Mid/Senior Data Engineer

Role Description

We are looking for a Mid/Senior Data Engineer to join our Data Engineering practice and help clients build modern data foundations on Databricks and AWS.

• Design and build data pipelines that extract from enterprise ERP systems, transform through medallion architectures, and deliver governed, AI-ready data products.
• Work directly with client subject-matter experts to understand business domains, validate data models, and ensure the platform is production-grade from day one.
• Current engagements involve regulated manufacturing environments where data governance, quality management, and traceability are essential.
• This is a fully remote role with collaboration across distributed teams and daily overlap with the US Eastern Time Zone.

Qualifications

• 4–7+ years of experience as a Data Engineer or in a closely related role.
• Strong programming skills in Python, including PySpark.
• Solid SQL skills including complex analytical queries against large enterprise databases.
• Hands-on experience with Databricks: Delta Lake, Unity Catalog, Databricks Workflows, and SQL Warehouse.
• Working knowledge of AWS core services: S3, IAM, VPC, and networking fundamentals.
• Experience building ETL/ELT pipelines that extract from enterprise ERP or transactional systems (Oracle, SAP, Microsoft Dynamics, or similar).
• Strong understanding of data modeling, medallion architectures, and dimensional design.
• Experience with data quality frameworks: validation rules, anomaly detection, and exception handling.
• Experience using AI and LLM tools to accelerate engineering workflows — including deriving data contracts, mapping specifications, and schema documentation from database metadata and limited business context.
• Comfortable collaborating directly with business stakeholders and subject-matter experts, not just engineering teams.
• Ability to participate in technical discussions, code reviews, and architectural decisions with confidence.
• Reliable high-speed internet and ability to work effectively in a remote-first environment.
• Daily overlap with US Eastern Time Zone.

Requirements

• Familiarity with Oracle E-Business Suite table structures and data patterns (INV, PO, BOM, WIP modules).
• Exposure to manufacturing domain concepts: bills of material, work orders, production routing, inventory management.
• Experience with dbt for data transformation and data product development.
• Hands-on experience with data governance and catalog tooling (Unity Catalog, AWS Glue/Datazone, Apache Atlas, or similar).
• Multi-system data integration or ERP consolidation experience, reconciling different source schemas into a unified canonical model.
• Spec-driven or contract-driven development methodology, YAML specifications, schema validation, data contracts.
• Experience in medical device, pharmaceutical, or other regulated manufacturing environments.
• Databricks Asset Bundles and CI/CD automation for data platform deployments.
• Familiarity with Apache Iceberg or Delta Lake UniForm for open table format interoperability.
• Experience supporting AI/ML workflows in production: feature engineering, model serving integration, or AI-ready data product design.

Benefits

• Building data foundations that power AI, analytics, and operational decision-making for manufacturing enterprises.
• Working directly with domain experts to understand how real businesses operate, not just pushing data through pipes.
• Solving multi-system integration challenges where no two ERPs store data the same way.
• Designing platforms with governance, observability, and data quality built in from the outset.
• Contributing to a reusable platform accelerator that will be deployed across multiple client engagements.
• Raising the bar for how data engineering is done: spec-driven, tested, version-controlled, and production-grade.