Data Engineer

Position Summary

As a Data Engineer, you will own the data platform that powers everything from streaming feature pipelines for machine learning models to executive analytics dashboards. You will design and maintain scalable ETL and ELT pipelines using Python, Apache Spark, and Airflow, optimize cloud data warehousing on Snowflake and AWS Redshift, and partner closely with data scientists, ML engineers, and product teams. This is a highly leverageable role where clean, reliable, and fast data translates directly into better AI products.

Key Responsibilities

• ✓ Design, build, and maintain scalable data pipelines that ingest, transform, and load data from dozens of sources into Snowflake and AWS Redshift warehouses using Python, Apache Spark, and Airflow.
• ✓ Develop and operate robust ETL/ELT workflows that support machine learning model training, feature engineering, and real-time analytics workloads.
• ✓ Optimize warehouse performance, query efficiency, and storage costs through thoughtful data modeling, partitioning, clustering, and incremental processing strategies.
• ✓ Implement data quality monitoring, alerting, and lineage tracking to ensure accuracy and reliability across the entire data environment.
• ✓ Collaborate with data scientists and ML engineers to provision reliable training and inference datasets, feature stores, and model evaluation data.
• ✓ Automate infrastructure and pipeline deployments with infrastructure-as-code tooling, CI/CD practices, and cloud-native services on AWS.
• ✓ Document data architecture, contribute to engineering standards, and mentor junior engineers as the data team grows.

Required Qualifications

• ✓ 5+ years of experience as a Data Engineer, big data engineer, or data pipeline engineer working in production environments.
• ✓ Strong programming skills in Python with experience writing production-grade data processing and orchestration code.
• ✓ Deep experience with Apache Spark (PySpark) for processing large-scale batch and streaming datasets.
• ✓ Hands-on experience building and managing workflows with Apache Airflow, including DAG design, scheduling, and monitoring.
• ✓ Proficiency with modern cloud data warehouses such as Snowflake and AWS Redshift, including SQL optimization, data modeling, and ELT patterns.
• ✓ Solid understanding of data warehousing concepts, dimensional modeling, lakehouse architectures, and big data technologies.
• ✓ Experience with AWS services such as S3, EC2, EMR, Lambda, and Glue, plus a strong grasp of version control and CI/CD workflows.

Preferred & Nice-to-Have

• ✓ Experience with streaming technologies such as Apache Kafka, Kinesis, Flink, or real-time feature pipelines.
• ✓ Familiarity with dbt, Airbyte, or other modern data transformation and ingestion frameworks.
• ✓ Background in machine learning infrastructure, feature stores, or serving data to ML models in production.
• ✓ Experience with Kubernetes, Terraform, and Infrastructure-as-Code for deploying data platforms.

Benefits

This full-time Data Engineer position comes with a comprehensive benefits package, including competitive base salary of $145,000 - $170,000, meaningful equity in a fast-growing startup, medical/dental/vision insurance, 401(k) with company match, flexible PTO, remote-friendly hybrid work in San Francisco, professional development budget, and accelerated career growth as the company scales.

How to Apply

Ready to build the data platforms powering the next generation of AI? Submit your resume through the ITTechnica contact page referencing Job ID ITT-2026-004. Our dedicated recruiting team will review your application, get back to you within 48 hours, and guide you through every step of the interview and offer process. Candidates experience no fees — ever.