Senior Data Engineer

Role Description

As a Senior Data Engineer , you will play a critical role in designing, building, and maintaining the data infrastructure that powers analytics solutions across a variety of enterprise client environments. This role combines modern data engineering practices with strong database and data quality fundamentals. You will be responsible for:

• Building scalable ETL/ELT pipelines
• Designing robust data models
• Integrating data from diverse platforms
• Ensuring reliable, well-documented data foundations

You'll work primarily within Microsoft Fabric environments while collaborating closely with analytics, engineering, and client stakeholders to deliver high-quality, production-ready data solutions.

What you will do

• Design, build, and maintain ETL/ELT pipelines for enterprise data ingestion and transformation across multiple client environments.
• Develop and maintain SQL views, schemas, and transformation logic for Power BI and other analytics solutions.
• Profile source data, identifying data quality issues, anomalies, duplicates, null values, and integrity concerns.
• Produce and maintain comprehensive data dictionaries, lineage documentation, and transformation documentation for every engagement.
• Build and manage data pipelines primarily within Microsoft Fabric while supporting Databricks and other client-specific environments as needed.
• Integrate data from REST APIs, GraphQL endpoints, and webhook-based sources, implementing authentication, pagination, rate-limiting, and error handling.
• Implement monitoring, alerting, and refresh processes to proactively identify and resolve pipeline failures.
• Validate data integrity throughout development to ensure reliable and accurate downstream analytics.
• Translate client business requirements into scalable technical data models while identifying limitations and gaps within source systems.
• Collaborate closely with visualization developers to ensure the data layer supports reporting and analytics requirements.
• Create and maintain clear handoff documentation, architecture documentation, and operational runbooks.
• Mentor junior engineers and contribute to engineering best practices, documentation standards, and delivery excellence.
• Participate in engagement planning, solution design, and project execution from kickoff through delivery.

Qualifications

• 8+ years of professional experience in Data Engineering, Backend Platform Engineering, or large-scale data infrastructure.
• 3+ years of experience in client-facing or consulting-focused data engineering environments.
• Advanced SQL expertise, including schema design, query optimization, complex views, CTEs, window functions, deduplication strategies, and data modeling.
• Strong Python experience for ETL development, automation, PySpark, and data processing workflows.
• Hands-on experience building and maintaining enterprise-scale ETL/ELT pipelines in production environments.
• Experience integrating data from REST APIs, GraphQL endpoints, and webhook-based systems.
• Strong understanding of data quality practices, validation processes, anomaly detection, and data governance.
• Experience working across multiple concurrent client engagements with varying levels of data maturity.
• Excellent documentation and communication skills, including data dictionaries, lineage documentation, and technical handoffs.
• Strong ownership mindset and the ability to operate independently in fast-paced environments.

Benefits

• Remote work options
• Competitive pay range: $70 - $70 USD

Our Values

We strive to deliver exceptional quality and consistency through a white-glove approach. The values we live by include:

• Customer-centric Solutions
• Innovation & Excellence
• Integrity & Transparency
• Data-driven Decision Making

Need to Know

The posting will be active for a minimum of 3 days. The active posting will continue to extend by 3 days until the position is filled. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.