> Markdown version of [/jobs/ext/4721976-manufacturing-data-engineer](https://www.wearedevelopers.com/jobs/ext/4721976-manufacturing-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Manufacturing Data Engineer

- **Company:** Kforce Inc.
- **Location:** Foster City, CA, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Information Systems, Continuous Integration, Data as a Services, Data Dictionary, Information Engineering, Data Governance, Dimensional Modeling, Github, Identity and Access Management, JSON, Python (Programming Language), OAuth, Performance Tuning, Standard Sql, SAP (Applications), SQL Databases, Data Streaming, Technical Data Management Systems, Large Language Models, Apache Spark, Data Lakes, Pyspark, Semi-structured Data, Git Flow, Information Technology, Terraform, Data Pipelines, Databricks
- **Published:** November 14, 2026
- **Apply:** https://www.dice.com/job-detail/2070de87-cfec-4f26-acd2-a47e74b4e54c

## About the Role

* Bachelor's degree in Computer Science, Information Systems, Engineering or a related field, or equivalent practical experience, plus 6+ years in data engineering
 * Strong SQL and Python, including PySpark
 * Hands-on production experience on Databricks: Delta Lake, Unity Catalog permissions, Workflows or jobs, and Spark performance tuning
 * Production experience with dbt, including incremental models and tests
 * Solid grasp of dimensional modeling, the medallion pattern, and CDC and incremental loading
 * Experience deploying data code through Git-based workflows and CI/CD (e.g., GitHub Actions, Databricks Asset Bundles or similar)
 * Working knowledge of AWS data services (S3, IAM, DMS or Kinesis) and infrastructure as code (e.g., Terraform)

Preferred Qualifications:

 * Databricks Certified Data Engineer Associate or Professional; AWS certification (e.g., Solutions Architect Associate) a plus
 * Experience preparing data for Databricks AI/BI dashboards, Genie, or ML and LLM use cases
 * Background in manufacturing or industrial data, such as quality, yield, traceability or MES
 * Understanding of data governance and compliance as they relate to data pipelines

## Description

Kforce has a client that is seeking a Manufacturing Data Engineer in Foster City, CA., * Build batch and streaming ingestion into Delta Lake using Auto Loader, Lakeflow Declarative Pipelines, Lakeflow Connect or Structured Streaming, including CDC feeds from AWS DMS and SAP SLT

 * Design and maintain bronze, silver and gold (medallion) layers that follow MOPS naming conventions and data dictionary standards
 * Build incremental dbt models on Databricks (dbt-databricks), using MERGE and upsert patterns, SCD Type 2, and handling for late or out-of-order records
 * Model manufacturing data for analytics, such as a single source of truth per unit (SFC), work orders, nonconformances, station results and first-pass yield, and feed the semantic layer used by analysts
 * Process large and semi-structured data, such as JSON test payloads, using PySpark and Databricks SQL
 * Tune pipeline performance and cost through liquid clustering or partitioning, OPTIMIZE, VACUUM, file sizing and right-sized job compute
 * Own data quality with dbt tests, Lakeflow expectations and Lakehouse Monitoring, including freshness SLAs and alerting
 * Orchestrate workloads with Databricks Workflows or Airflow
 * Migrate existing Redshift models and pipelines to Databricks: translate SQL, run in parallel, reconcile results and cut over
 * Partner with analysts and manufacturing stakeholders on requirements, and document lineage, data contracts and table definitions in Unity Catalog
 * Build and maintain CI/CD for MOPS jobs, pipelines and dbt models with Databricks Asset Bundles and GitHub Actions, across dev, staging and prod
 * Manage MOPS-owned catalogs, schemas, volumes and grants in Unity Catalog, following the central platform team's governance model
 * Configure job compute and SQL warehouses within central cluster policies; Manage MOPS service principals, secret scopes and OAuth machine-to-machine auth for Airflow and dbt