Senior Data Engineer

Summary of Position

We are seeking an experienced Senior Data Engineer to design, build, and maintain scalable data pipelines, data platforms, and analytical data products. The Data Engineer will collaborate with data architects, data scientists, analysts, application teams, and business stakeholders to deliver trusted data for analytics, reporting, machine learning, and operational use cases.
The ideal candidate has strong experience with modern cloud data platforms, data integration, data modeling, distributed processing, data quality, and governance. Experience with Databricks, Snowflake, Microsoft Fabric, Azure, or similar cloud platforms is highly desirable.

Work Schedule: M - F 8am - 5pm. This is a hybrid position: 4 days onsite, 1 day remote.

Essential Functions

• Data Engineering & Platform Development:
  • Design, develop, and maintain scalable batch and real-time data pipelines.
  • Build reliable ETL/ELT processes for structured, semi-structured, and unstructured data.
  • Integrate data from databases, APIs, SaaS applications, files, and event streams.
  • Develop and maintain cloud-based data lake, lakehouse, and data warehouse solutions.
  • Work with technologies such as Databricks, Snowflake, Microsoft Fabric, Azure Data Factory, Spark, SQL, and cloud storage.
  • Implement reusable data engineering frameworks, patterns, and standards.
  • Support data platform modernization and migration initiatives.
• Data Modeling & Data Products:
  • Design logical and physical data models for analytical and operational use cases.
  • Develop dimensional, normalized, and lakehouse data models.
  • Build curated data layers supporting reporting, analytics, and machine learning.
  • Support domain-oriented data products within a data mesh operating model.
• Data Quality, Governance & Security:
  • Implement data validation, quality checks, reconciliation, monitoring, and alerting.
  • Support data cataloging, metadata management, lineage, and data ownership.
  • Implement appropriate security, access controls, privacy, and regulatory requirements.
  • Establish monitoring and operational processes for production data pipelines.
• Performance & Cost Optimization:
  • Optimize data pipelines, queries, storage, and compute workloads.
  • Apply appropriate partitioning, clustering, caching, and workload-management techniques.
  • Identify opportunities to improve platform performance, scalability, reliability, and total cost of ownership.
• Collaboration & Delivery:
  • Partner with architects, data scientists, analytics engineers, BI developers, application developers, and business stakeholders.
  • Translate business requirements into scalable technical solutions.
  • Participate in architecture reviews, technical design sessions, code reviews, and Agile delivery.
  • Create technical documentation and operational runbooks.
  • Mentor junior engineers and promote engineering best practices.
  • Must maintain operational compliance with US and international regulatory agencies and guidelines (i.e. FDA, DEA, EU, HC, TGA, PIC/S, ISO, USP, NRC, cGMP, etc.).

Requirements

• Must have Experience / Skills:
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent experience.
  • 5+ years of professional data engineering experience.
  • Strong SQL and database development skills.
  • Experience developing production-grade ETL/ELT pipelines.
  • Proficiency in Python, Scala, Java, or similar programming language.
  • Experience with cloud data platforms and cloud storage.
  • Strong understanding of data modeling, data warehouses, data lakes, and/or lakehouses.
  • Experience with Git, CI/CD, testing, and deployment practices.
• Nice to have Experience / Skills:
  • Hands-on experience with Databricks, Snowflake, or Microsoft Fabric.
  • Experience with Apache Spark / PySpark and distributed data processing.
  • Experience with Azure, AWS, or Google Cloud.
  • Experience with streaming technologies such as Kafka, Event Hubs, or Kinesis.
  • Experience with orchestration tools such as Azure Data Factory, Airflow, or similar.
  • Experience with Delta Lake, Apache Iceberg, or other open table formats.
  • Experience implementing data mesh, domain-oriented data products, or federated data architectures.
  • Experience with data catalog, lineage, governance, and observability platforms.
  • Experience supporting AI/ML data workloads.
  • Industry certifications or training in data engineering, cloud platforms, master data management, analytics, or project management.
  • Experience with pharmaceutical regulatory guidelines, including electronic records and signatures, data integrity, cGMP, FDA 21 CFR Parts 11, 210, and 211, EU Annex 11, MHRA, and GAMP 5.
  • Additional languages a Plus

Working Conditions:

• This position will work in typical office conditions with extensive time using computer equipment.
• Close attention to detail required.
• Willingness to work in a team-based environment.
• May be required to sit or stand for long periods of 8+ hours a day while performing duties.  
• Must possess good hand-eye coordination; close attention to detail is required.
• Willingness to complete safety training within allotted timeframes, and work in a team-based environment.
• The position deals with many deadlines. Must be able to work outside of regular work hours, including off shift, weekend, and holiday work as business needs require.