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# Data Engineer

- **Company:** SSTech LLC
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Unity 3d, Query Performance, Artificial Intelligence, Airflow, Microsoft Azure, Batch Processing, Big Data, Data as a Services, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, Database Queries, Dimensional Modeling, Python (Programming Language), Meta-Data Management, Query Optimization, Scala (Programming Language), SQL Databases, Data Streaming, Data Processing, Snowflake, Apache Spark, Git, Data Lakes, Pyspark, Luigi, Star Schema, Spark Streaming, Data Management, Virtual Agents, Data Pipelines, Jenkins, Databricks
- **Published:** June 30, 2026
- **Apply:** https://www.dice.com/job-detail/5290d1ca-9b84-4dbe-a79c-6b2939c914d0

## About the Role

Primary Platforms: Palantir Foundry, Databricks, Snowflake, IBM WatsonX.data
Programming: Python, PySpark, SQL, Scala
Data Processing: ETL/ELT pipelines, real-time streaming, batch processing
Cloud: Azure (Data Factory, Synapse, ADLS), Databricks, Snowflake
Tools: Airflow, dbt, Apache Spark, Delta Lake, Unity Catalog, 3+ years of hands-on data engineering experience
Expert-level proficiency in Python and PySpark for data processing
Strong SQL skills with experience in complex query optimization
Hands-on experience with at least two of: Palantir Foundry, Databricks, Snowflake
Experience with cloud platforms (Azure) and their data services
Knowledge of data modeling (dimensional modeling, star schema, snowflake schema)
Experience with orchestration tools (Airflow, dbt, Luigi, or similar)
Strong understanding of data governance, security, and compliance requirements
Preferred Qualifications:
Experience with IBM WatsonX.data or similar AI data platforms
Knowledge of Delta Lake, Iceberg, or similar lakehouse formats
Experience with GenAI, RAG architectures, or LangChain
Familiarity with MCP (Model Context Protocol) for AI agent integrations

## Description

Position Overview: We are seeking an experienced Senior Data Engineer to design, build, and maintain enterprise-scale data platforms using modern cloud-native technologies. The ideal candidate will have deep expertise in Palantir Foundry, Databricks, and/or Snowflake, with a strong background in building scalable ETL/ELT pipelines and data warehousing solutions., Design and implement end-to-end data pipelines using Palantir Foundry, Databricks, and Snowflake
Develop scalable ETL/ELT workflows using Python, PySpark, and SQL for processing large-scale datasets
Build and maintain data lake and data warehouse architectures on cloud platforms (Azure (Data Factory, Synapse, ADLS), Databricks, Snowflake)
Implement data governance, quality checks, and metadata management frameworks
Create and optimize Databricks notebooks, Delta Lake tables, and Unity Catalog implementations
Design Palantir Foundry Ontologies, and transformation pipelines
Collaborate with data scientists, analysts, and business stakeholders to deliver data products
Optimize query performance and storage strategies in Snowflake (clustering, partitioning, materialized views)
Implement real-time streaming pipelines using Spark Streaming, or similar technologies
Develop CI/CD pipelines for data workflows using Git, Jenkins, or similar tools


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