Data Engineer

Position Overview We are seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines and warehouse infrastructure that power critical business analytics and decision-making. The ideal candidate combines deep Python expertise with hands-on data warehouse experience and brings a passion for transforming raw data into reliable, well-modeled assets. Experience with Palantir Foundry is a strong differentiator for this role. Key Responsibilities • Design, develop, and optimize ETL/ELT pipelines to ingest, transform, and load data from diverse sources into cloud-based data warehouse environments • Build and maintain dimensional data models, schemas, and table structures that support reporting, analytics, and machine learning workloads • Write clean, production-grade Python code for data transformation, validation, orchestration, and automation tasks • Develop and manage data workflows within Palantir Foundry, including ontology design, pipeline configuration, and dataset governance (preferred) • Collaborate with data analysts, data scientists, and business stakeholders to translate requirements into robust data solutions • Implement data quality frameworks including monitoring, alerting, testing, and lineage tracking • Optimize query performance and storage efficiency across warehouse platforms (e.g., Snowflake, Redshift, BigQuery, or Databricks) • Contribute to infrastructure-as-code practices, CI/CD pipelines, and version control standards for data assets Required Qualifications • Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field • 3+ years of professional experience in a Data Engineering or similar data-focused role • Strong proficiency in Python, including libraries such as Pandas, PySpark, SQLAlchemy, or Airflow • Solid experience designing and working within enterprise data warehouse environments (Snowflake, Redshift, BigQuery, or equivalent) • Advanced SQL skills with the ability to write complex queries, optimize performance, and model data effectively • Familiarity with orchestration tools (Apache Airflow, Prefect, Dagster, or similar) • Experience with cloud platforms (AWS, Azure, or GCP) and related data services • Strong understanding of data modeling concepts (star schema, snowflake schema, data vault) Preferred Qualifications • Hands-on experience with Palantir Foundry, including pipeline development, ontology management, and Foundry-native transforms • Experience with real-time or streaming data pipelines (Kafka, Kinesis, Spark Streaming) • Familiarity with containerization (Docker) and orchestration (Kubernetes) • Knowledge of data governance, data cataloging, and metadata management tools • Prior experience in a regulated industry (defense, healthcare, finance) is a plus What We Offer • Competitive salary and comprehensive benefits package • Opportunity to work with cutting-edge data platforms and technologies • Collaborative, innovation-driven team culture • Professional development support and career growth pathways