Senior Data Engineer (Contract)

Senior Data Engineer
Position Overview

We are seeking a Senior Data Engineer for a long-term contract opportunity. This role will support a reporting and analytics team responsible for data used in digital administration, operational reporting, post-administration analysis, and leadership insights.

The ideal candidate will have deep experience with complex SQL, Python, cloud data platforms, data quality engineering, and large-scale reporting datasets. This role is focused on ensuring that critical reporting data is accurate, complete, timely, and trustworthy.
Location and Work Arrangement

• Role Type: Long-term contract
• Location: Remote
• Hours: Must be available during EST business hours
• Work Authorization: Visa candidates are acceptable

About the Role

As a Senior Data Engineer, you will help ensure that the data powering products, reporting, and operational workflows is reliable and production-ready. You will design and implement data quality checks, monitoring, reconciliation processes, and remediation workflows across data pipelines and platforms.

This role blends hands-on technical investigation, automation, data analysis, and collaboration with engineering, analytics, product, and business teams.
Key Responsibilities
Data Quality Engineering and Monitoring

• Design and implement automated data quality checks for completeness, accuracy, consistency, freshness, and schema integrity across critical datasets and pipelines.
• Build monitoring, alerting, and observability solutions to detect anomalies, pipeline failures, data drift, and unexpected changes before they impact downstream users.
• Develop and maintain reconciliation processes across source systems, transformed datasets, reports, and operational outputs.
• Partner with engineers and analysts to define quality rules, acceptance criteria, and validation requirements for new and existing systems.
• Create reusable frameworks, scripts, and tooling for profiling, testing, and validating data in production and non-production environments.

Investigation, Analysis, and Remediation

• Investigate data issues by tracing data across systems, transformations, and business workflows to identify root causes and recommend fixes.
• Use SQL, Python, and cloud data tools to analyze large datasets, isolate anomalies, and validate business logic.
• Support incident response and issue resolution for data-related production problems, especially during high-priority operational periods.
• Work with cross-functional teams to remediate defects, improve upstream processes, and reduce recurrence of common data issues.
• Communicate findings clearly to technical and non-technical stakeholders, including issue summaries, remediation recommendations, and quality trends.

Governance, Documentation, and Team Success

• Document data definitions, validation logic, lineage, quality rules, and remediation procedures.
• Contribute to best practices for testing, version control, deployment, and ongoing maintenance of data quality solutions.
• Participate in Agile ceremonies, code reviews, and team planning.
• Support standards for data governance, ownership, and operational excellence.
• Partner with stakeholders to improve trust in shared data assets and ensure data quality is built into delivery from the start.

Required Qualifications

• Bachelor's degree in Engineering, Computer Science, a related field, or equivalent professional experience.
• 10+ years of general experience in quality testing, data quality, data engineering, analytics engineering, software engineering, or a related discipline.
• Strong SQL skills with experience writing complex queries to analyze, validate, and troubleshoot data across multiple systems.
• Professional experience working with large datasets and production data pipelines.
• Experience designing or maintaining data quality checks, monitoring, alerting, or observability processes for production datasets or pipelines.
• Proficiency in Python or TypeScript for automation, testing, and data analysis.
• Experience with cloud data platforms and tools such as AWS, Redshift, Athena, Snowflake, Databricks, or similar technologies.
• Strong understanding of data structures, data modeling, transformations, lineage, and common sources of data defects.
• Ability to investigate issues across systems, apply business logic, and translate ambiguous problems into structured analysis and action.
• Experience with BI and reporting tools such as Tableau, QuickSight, or similar platforms.
• Exposure to AI-assisted development tools and hands-on experience applying AI tools to support automation, coding, testing workflows, or data pipeline activities.
• Ability to support high-priority operational periods and respond effectively to production data issues when needed.

Preferred Qualifications

• Experience with digital administration, operational reporting, or high-volume event-based reporting environments.
• Hands-on experience with Apache Spark or other big data processing frameworks.
• Experience building reusable validation frameworks or automated data quality tooling.
• Experience with Tableau AI, Amazon Q, Google Cloud AI, Google Cloud Smart Analytics, GitHub Copilot, Claude, or similar AI-assisted tools.
• Experience with Tableau Desktop / Creator or Amazon QuickSight.
• Familiarity with AWS Glue, Lambda, SNS, and SQS.

Tech Stack Grid

Technology / Skill Expected Level 1-5

SQL 5

Python 5

Redshift 5

Microsoft Excel 4

AI Tools 3

AWS S3 3

AWS Glue 3

AWS Athena 2

Tableau Desktop / Creator 2

Amazon QuickSight 2

AWS Lambda 1

AWS SNS / SQS 1
Tools and Platforms

Category Tools / Technologies

Data Warehousing and Querying SQL, Amazon Redshift, Amazon Athena, Snowflake, Databricks

Cloud and Storage AWS S3, AWS Glue, AWS Lambda, AWS SNS, AWS SQS

Data Processing Apache Spark

BI and Reporting Tableau Desktop / Creator, Amazon QuickSight

Automation and Analysis Python, TypeScript, Microsoft Excel

AI-Assisted Tools Amazon Q, Google Cloud AI, Google Cloud Smart Analytics, Tableau AI, GitHub Copilot, Claude

Data Quality Automated validation, reconciliation, monitoring, alerting, observability, lineage documentation
Ideal Candidate Profile

The ideal candidate is a hands-on data professional with advanced SQL expertise, strong Python automation skills, and experience supporting data quality for large reporting datasets. They should be comfortable tracing data issues across systems, validating complex business logic, building automated checks, and improving trust in data used for operational and leadership reporting.

Pay Rate Range: $80-$90 per hr (Depending on Experience)

nextSource is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, marital status, parental status, cultural background, organizational level, work styles, tenure, and life experiences or for any other reason.

nextSource is committed to providing reasonable accommodation for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, you may contact us at

What nextSource Provides:

• Healthcare Benefits including Medical, Prescription, Vision & Dental Coverage | United Healthcare
• Voluntary STD & LTD | New York Life
• 401(k) Retirement Planning | Fidelity
• Discount Program

*You are Eligible to participate in the benefits program if you are considered a full-time employee of nextSource, working at least 30 hours per week on a consistent basis. Your coverage will be effective on the 1st of the month following 60 days of employment.

• Published on 08 Jun 2026, 5:58 PM