Senior Analytics Data Engineer- W2 Only

Role: Senior Analytics Data Engineer
Location: Rockville, MD
Duration: 12-month base contract; long-term extensions

Job Description:
Senior Data Engineer – Engineering Metrics & Analytics
We are looking for a hands-on Senior Data Engineer to develop and maintain an engineering metrics and analytics platform. The platform integrates data from multiple engineering systems, including Jira, Bitbucket, GitLab, Jenkins, deployment systems, and Splunk.
The candidate must be capable of independently understanding complex datasets, building reliable data pipelines, identifying and resolving data quality issues, performing analytics, and delivering dashboards or lightweight applications to present actionable engineering insights.
This is a hands-on engineering role requiring strong technical skills, analytical thinking, ownership, and the ability to guide junior team members.

Mandatory Technical Requirements
1. Data Engineering
Strong Python programming and advanced SQL skills.
Experience building ETL/ELT pipelines to integrate multiple data sources.
Experience with data transformation, aggregation, data modeling, and pipeline optimization.
Knowledge of REST APIs, authentication, pagination, rate limits, and error handling.
Experience handling large datasets, incremental loads, and changing source schemas.

2. Data Quality and Reliability
Experience implementing automated data validation and reconciliation.
Ability to identify missing, duplicate, inconsistent, and inaccurate records.
Experience investigating root causes of data discrepancies.
Ability to build data-quality checks, exception reports, monitoring, and alerting.
Understanding of data lineage, metric definitions, and data consistency across source systems.

3. Data Analytics
Ability to analyze complex datasets and independently derive meaningful insights.
Experience defining and calculating KPIs using clear, consistent business rules.
Ability to investigate unexpected metrics and distinguish genuine trends from data issues.
Strong analytical reasoning and problem-solving skills.

4. Dashboard and Application Development
Experience developing interactive dashboards using Quick, Grafana, Splunk, Power BI or custom webapp, or a comparable tool.
Ability to build appropriate visualizations, filters, drill-downs, and trend analysis.
Experience developing lightweight data applications using Python frameworks such as Streamlit or Dash, or an equivalent technology, where required.

5. Engineering Practices and Ownership
Strong debugging, code review, testing, documentation, and version control practices.
Ability to work independently with ambiguous requirements and deliver end-to-end solutions.
Experience mentoring junior developers and establishing reusable engineering standards.
Ability to explain technical findings and data-quality issues clearly to stakeholders.

Preferred Experience
Integration with Jira, Bitbucket, GitLab, Jenkins, Splunk, and deployment systems.
Understanding of software delivery lifecycle metrics, including DORA metrics.
Experience with cloud platforms, workflow orchestration, and production data pipeline monitoring.
Experience supporting engineering productivity, DevOps analytics, or developer experience initiatives.

Experience Level
Ideally 8-15 years of relevant hands-on experience, with demonstrated senior-level ownership of data engineering and analytics solutions.

Candidate Evaluation
End-to-end ownership of a multi-source data integration solution.
Practical experience resolving complex data-quality issues.
Strong SQL and Python development skills. Dashboard development and analytical problem-solving experience.
The ability to work independently, make technical decisions, and mentor junior team members.
Please include examples of comparable projects, the candidate’s specific contributions, and their proficiency in Python, SQL, data quality engineering, APIs, and dashboard development.