Is the Senior Data Engineer (Remote) position at Neumo Holdings LLC fully remote?

Yes, this Senior Data Engineer (Remote) position at Neumo Holdings LLC is a remote position. The role is available for candidates in United States.

Is this a full-time or part-time Senior Data Engineer (Remote) role?

This is a full-time Senior Data Engineer (Remote) position at Neumo Holdings LLC.

What are the main requirements for the Senior Data Engineer (Remote) role?

Key requirements include: at the senior level, mentor other contributors and raise the overall data engineering practice of the team., perform other duties as assigned., bachelor's degree in computer science, information systems, engineering, or a related technical field; equivalent professional experience will be considered in lieu of a degree., and more.

How do I apply for the Senior Data Engineer (Remote) position at Neumo Holdings LLC?

You can apply for this Senior Data Engineer (Remote) position by clicking the "Apply Now" button on this page, which will take you to Neumo Holdings LLC's application portal.

Senior Data Engineer (Remote) at Neumo Holdings LLC

United States

<div><div><h2 dir="ltr" data-pasted="true"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Job Summary:</span></h2><p dir="ltr"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Our Revenue Compliance platforms generate a large and growing volume of tax, licensing, and compliance data. Today, much of the work of moving, reconciling, and reporting on that data depends on legacy tooling and manual steps.</span></p><p dir="ltr"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>The Data Engineer designs and builds the pipelines and data models that our reporting, analytics, and emerging AI initiatives depend on, and retires the manual and legacy processes those functions rely on today. The role also supports the data side of our migration to Amazon Aurora, ensuring that downstream reporting and extracts move cleanly as source systems change. This is a foundational position with wide scope and real constraints, suited to an engineer who wants to define how a data platform gets built rather than maintain an existing design.</span></p><h2 dir="ltr"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Duties and Responsibilities:</span></h2><ul dir="ltr"><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Design, implement, and operate ETL and ELT pipelines that move data from transactional systems into analytical and reporting environments on schedule, with monitoring and alerting sufficient to establish confidence in the results.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Replace legacy and manual data processes with maintainable, version-controlled, tested pipelines, reducing the number of steps that depend on an individual remembering a procedure.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Design warehouse schemas and data models that make reporting consistent across products rather than requiring each report to define its own logic.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Support the Amazon Aurora migration by ensuring downstream pipelines, extracts, and reporting move cleanly as source systems migrate, and by validating data integrity through cutover.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Build validation, reconciliation, and alerting into pipelines so that data quality issues are identified before a customer or auditor encounters them.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Partner with architecture and AI initiatives to prepare clean, well-structured, and well-documented datasets that enable downstream analytical and machine learning work.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Work with application engineers, the database administrator, site reliability, and business stakeholders to establish what the data means, not solely where it resides.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Maintain clear documentation of data sources, lineage, and business definitions.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Translate ambiguous business questions into concrete data requirements, and exercise independent judgment in selecting the appropriate technical approach.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>At the senior level, mentor other contributors and raise the overall data engineering practice of the team.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Perform other duties as assigned.</li></ul><h2 dir="ltr"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Education and Experience:</span></h2><ul dir="ltr"><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field; equivalent professional experience will be considered in lieu of a degree.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Four to eight years of data engineering experience, including production ownership of pipelines the candidate personally designed and built.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Demonstrated experience designing and operating ETL and ELT pipelines, including orchestration, scheduling, error handling, and retry logic.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Hands-on experience with a cloud data platform. AWS preferred; Azure or GCP considered.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Data warehouse and dimensional modeling experience sufficient to defend schema design decisions.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Experience applying version control and CI/CD practices to data work, not solely to application code.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Experience with AWS-native data tooling such as Glue, DMS, S3, Redshift, Athena, Lambda, or Step Functions.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Experience with pipeline orchestration frameworks such as Airflow, Dagster, or Prefect, and with transformation tooling such as dbt.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Experience migrating reporting and analytics workloads alongside a database platform migration.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Experience replacing legacy or low-code data tooling such as Alteryx or SSIS with engineered pipelines.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Experience preparing data foundations for machine learning or AI use cases.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Background in tax, financial services, government technology, or another regulated, audit-sensitive domain.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Experience with data governance, lineage, and cataloging practices.</li></ul><h2 dir="ltr"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Knowledge, Skills and Abilities:</span></h2><ul dir="ltr"><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Advanced SQL, including complex joins, window functions, and query optimization, together with the judgment to recognize when a query is the wrong tool.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Strong Python for data engineering, using pandas, SQLAlchemy, or equivalent libraries, and general scripting proficiency.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Working knowledge of relational database platforms such as MySQL, MariaDB, SQL Server, or PostgreSQL.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Knowledge of dimensional modeling and data warehouse design principles.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Ability to translate ambiguous business questions into concrete, testable data requirements.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Ability to design and defend technical approaches independently, and to make architectural decisions with limited supervision.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Clear written communication, including the ability to produce documentation that others can rely on without follow-up.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Ability to collaborate effectively with engineering, reliability, and business stakeholders in a fully remote environment.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Knowledge of data quality, reconciliation, and observability practices for production pipelines.</li><li style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Ability to mentor other engineers and establish shared standards across a team.</li></ul><p><br><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'><strong>Work Environment</strong>:</span></p><div style="margin-left:0in;"><ul style="list-style-type: disc;"><li style='margin-left: 0in; font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Office setting with a moderate noise level.</li><li style='margin-left: 0in; font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>The employee will work at an individual workstation, using a telephone and computer.</li></ul></div><p style="margin-left:0in;"><br><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'><strong>Physical Demands</strong>:</span></p><div style="margin-left:0in;"><ul style="list-style-type: disc;"><li style='margin-left: 0in; font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Must be able to remain seated for extended periods.</li><li style='margin-left: 0in; font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Regular use of a computer and other office machinery, such as printers and copy machines.</li><li style='margin-left: 0in; font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Occasional movement around the office.</li><li style='margin-left: 0in; font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Frequent communication via telephone.</li></ul></div><p style="margin-left:0in;"><br><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'><strong>Neumo Summary:</strong></span></p><p style="margin-left:0in;"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>With the backing of four decades of public sector expertise and corporate capability, Neumo has successfully supported government services. Neumo was honored and recognized for four (4) consecutive years as a GovTech 100 Company representing the top 100 companies focused on making a difference in and selling to state and local government agencies across the United States.</span></p><p style="margin-left:0in;"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Neumo is committed to helping communities thrive and brings a wealth of experience combined with innovation. Today, Neumo offers more administrative and financial support to government officials than any other organization. And with a responsive, client-focused approach, we foster partnerships that give our customers the certainty they need to accomplish more.</span></p><p style="margin-left:0in;"><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Neumo offers a competitive benefits and compensation package and are looking for team members who will thrive in our dynamic environment.</span></p><p style="margin-left:0in;"><em><span style='font-family: "times new roman", serif; font-size: 16px; color: rgb(0, 0, 0);'>Neumo is an Equal Opportunity Employer. Selection for a position will be made without regard to race, religion, national origin, sex, political affiliation, marital status, non-disqualifying physical handicap, and age.</span></em></p></div></div>

Apply Now

Remote Opportunity

Senior Data Engineer (Remote)

Join Neumo Holdings LLC as a senior professional working remotely from United States. Explore the role, benefits, and apply in one place.

Senior Data Engineer (Remote)

Neumo Holdings LLC

Full Time

6 days ago

Job Summary: Our Revenue Compliance platforms generate a large and growing volume of tax, licensing, and compliance data. Today, much of the work of moving, reconciling, and reporting on that data depends on legacy tooling and manual steps.

United States

Engineering

Senior

Data engineering

ETL

ELT

+5 more

Job Description

Job Summary:

Our Revenue Compliance platforms generate a large and growing volume of tax, licensing, and compliance data. Today, much of the work of moving, reconciling, and reporting on that data depends on legacy tooling and manual steps.

The Data Engineer designs and builds the pipelines and data models that our reporting, analytics, and emerging AI initiatives depend on, and retires the manual and legacy processes those functions rely on today. The role also supports the data side of our migration to Amazon Aurora, ensuring that downstream reporting and extracts move cleanly as source systems change. This is a foundational position with wide scope and real constraints, suited to an engineer who wants to define how a data platform gets built rather than maintain an existing design.

Duties and Responsibilities:

Design, implement, and operate ETL and ELT pipelines that move data from transactional systems into analytical and reporting environments on schedule, with monitoring and alerting sufficient to establish confidence in the results.
Replace legacy and manual data processes with maintainable, version-controlled, tested pipelines, reducing the number of steps that depend on an individual remembering a procedure.
Design warehouse schemas and data models that make reporting consistent across products rather than requiring each report to define its own logic.
Support the Amazon Aurora migration by ensuring downstream pipelines, extracts, and reporting move cleanly as source systems migrate, and by validating data integrity through cutover.
Build validation, reconciliation, and alerting into pipelines so that data quality issues are identified before a customer or auditor encounters them.
Partner with architecture and AI initiatives to prepare clean, well-structured, and well-documented datasets that enable downstream analytical and machine learning work.
Work with application engineers, the database administrator, site reliability, and business stakeholders to establish what the data means, not solely where it resides.
Maintain clear documentation of data sources, lineage, and business definitions.
Translate ambiguous business questions into concrete data requirements, and exercise independent judgment in selecting the appropriate technical approach.
At the senior level, mentor other contributors and raise the overall data engineering practice of the team.
Perform other duties as assigned.

Education and Experience:

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field; equivalent professional experience will be considered in lieu of a degree.
Four to eight years of data engineering experience, including production ownership of pipelines the candidate personally designed and built.
Demonstrated experience designing and operating ETL and ELT pipelines, including orchestration, scheduling, error handling, and retry logic.
Hands-on experience with a cloud data platform. AWS preferred; Azure or GCP considered.
Data warehouse and dimensional modeling experience sufficient to defend schema design decisions.
Experience applying version control and CI/CD practices to data work, not solely to application code.
Experience with AWS-native data tooling such as Glue, DMS, S3, Redshift, Athena, Lambda, or Step Functions.
Experience with pipeline orchestration frameworks such as Airflow, Dagster, or Prefect, and with transformation tooling such as dbt.
Experience migrating reporting and analytics workloads alongside a database platform migration.
Experience replacing legacy or low-code data tooling such as Alteryx or SSIS with engineered pipelines.
Experience preparing data foundations for machine learning or AI use cases.
Background in tax, financial services, government technology, or another regulated, audit-sensitive domain.
Experience with data governance, lineage, and cataloging practices.

Knowledge, Skills and Abilities:

Advanced SQL, including complex joins, window functions, and query optimization, together with the judgment to recognize when a query is the wrong tool.
Strong Python for data engineering, using pandas, SQLAlchemy, or equivalent libraries, and general scripting proficiency.
Working knowledge of relational database platforms such as MySQL, MariaDB, SQL Server, or PostgreSQL.
Knowledge of dimensional modeling and data warehouse design principles.
Ability to translate ambiguous business questions into concrete, testable data requirements.
Ability to design and defend technical approaches independently, and to make architectural decisions with limited supervision.
Clear written communication, including the ability to produce documentation that others can rely on without follow-up.
Ability to collaborate effectively with engineering, reliability, and business stakeholders in a fully remote environment.
Knowledge of data quality, reconciliation, and observability practices for production pipelines.
Ability to mentor other engineers and establish shared standards across a team.

Work Environment:

Office setting with a moderate noise level.
The employee will work at an individual workstation, using a telephone and computer.

Physical Demands:

Must be able to remain seated for extended periods.
Regular use of a computer and other office machinery, such as printers and copy machines.
Occasional movement around the office.
Frequent communication via telephone.

Neumo Summary:

With the backing of four decades of public sector expertise and corporate capability, Neumo has successfully supported government services. Neumo was honored and recognized for four (4) consecutive years as a GovTech 100 Company representing the top 100 companies focused on making a difference in and selling to state and local government agencies across the United States.

Neumo is committed to helping communities thrive and brings a wealth of experience combined with innovation. Today, Neumo offers more administrative and financial support to government officials than any other organization. And with a responsive, client-focused approach, we foster partnerships that give our customers the certainty they need to accomplish more.

Neumo offers a competitive benefits and compensation package and are looking for team members who will thrive in our dynamic environment.

Neumo is an Equal Opportunity Employer. Selection for a position will be made without regard to race, religion, national origin, sex, political affiliation, marital status, non-disqualifying physical handicap, and age.

Requirements

at the senior level, mentor other contributors and raise the overall data engineering practice of the team.
perform other duties as assigned.
bachelor's degree in computer science, information systems, engineering, or a related technical field; equivalent professional experience will be considered in lieu of a degree.
four to eight years of data engineering experience, including production ownership of pipelines the candidate personally designed and built.
demonstrated experience designing and operating etl and elt pipelines, including orchestration, scheduling, error handling, and retry logic.
hands-on experience with a cloud data platform. aws preferred; azure or gcp considered.
data warehouse and dimensional modeling experience sufficient to defend schema design decisions.
experience applying version control and ci/cd practices to data work, not solely to application code.

Skills

Data engineering

ETL

ELT

SQL

Python

AWS

Data Modeling

Amazon Aurora

Ready to Apply?

Join Neumo Holdings LLC today

Posted 6 days ago

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