Job Description

Description

Hybrid 3 days onsite / 2 days remote in Rockville, MD

Our client seeks a hands-on Senior Data Engineer to design, build, and maintain an engineering metrics and analytics platform that integrates data from Jira, Bitbucket, GitLab, Jenkins, deployment systems, and Splunk. The role requires independent analysis of complex datasets, reliable data pipeline development, data quality remediation, analytics, and delivery of dashboards or lightweight applications that provide actionable engineering insights. The position requires strong technical skills, analytical thinking, ownership, and the ability to guide junior team members.

We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $45.00 to $55.00/hr. w2

Responsibilities

Develop and maintain ETL/ELT pipelines across multiple engineering data sources.
Model, transform, aggregate, and optimize data for analytics and reporting.
Implement automated data validation, reconciliation, monitoring, and alerting.
Investigate and resolve data quality issues including missing, duplicate, and inconsistent records.
Define and calculate KPIs with clear and consistent business rules.
Analyze datasets to derive insights and distinguish trends from data issues.
Build interactive dashboards and lightweight data applications to present insights.
Apply strong debugging, testing, documentation, and version control practices.
Work independently to deliver end-to-end solutions from ambiguous requirements.
Mentor junior developers and establish reusable engineering standards.
Communicate technical findings and data-quality issues to stakeholders.

Experience Requirements

Strong Python programming and advanced SQL skills.
Proven experience building ETL/ELT pipelines integrating multiple sources.
Hands-on work with REST APIs, authentication, pagination, rate limits, and error handling.
Experience with large datasets, incremental loads, and changing source schemas.
Automated data validation and reconciliation implementation experience.
Root-cause analysis for data discrepancies.
Dashboard development using tools such as Grafana, Splunk, Power BI, or custom web applications.
Experience with Python frameworks such as Streamlit or Dash for lightweight apps.
Strong analytical reasoning and problem-solving abilities.
Preferred: Integrations with Jira, Bitbucket, GitLab, Jenkins, Splunk, and deployment systems.
Preferred: Knowledge of software delivery lifecycle metrics, including DORA metrics.
Preferred: Experience with cloud platforms, workflow orchestration, and production pipeline monitoring.
Preferred: Support of engineering productivity, DevOps analytics, or developer experience initiatives.
Ideally 5–8+ years of relevant hands-on experience with senior-level ownership of data engineering and analytics solutions.

Education Requirements

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