Job description

About the Role

We are looking for a Senior or Lead Data Engineer to be the founding member of our new data team. In this high-impact role, you’ll report directly to the CTO and play a critical part in shaping the future of data at our company. You will work across three distinct product lines to standardize and unify data pipelines, processes, and governance. This is a unique opportunity to build from the ground up and influence data architecture and strategy at a multi-product SaaS company.

Responsibilities

• Design, build, and optimize scalable data pipelines using Apache Spark, Kafka, and related tools
• Develop and orchestrate data workflows using Apache Airflow
• Architect and manage infrastructure in AWS, including services like S3, Kinesis, Lambda, EMR, Glue, and Redshift
• Build and support real-time data pipelines and event-driven systems for streaming data ingestion and processing
• Establish standardized data ingestion, transformation, and storage processes across multiple product lines
• Work closely with product and engineering teams to unify and document data models and schemas
• Ensure data quality, lineage, and observability across all pipelines
• Lead data governance, compliance, and security practices from day one
• Mentor future hires and define engineering standards as the data team grows

Qualifications

• 5+ years of experience in data engineering, ideally in SaaS or multi-product environments
• Expertise in AWS services relevant to data infrastructure (S3, Glue, Redshift, EMR, Lambda, Kinesis, etc.)
• Strong proficiency in Python for building pipelines, ETL/ELT jobs, and infrastructure automation
• Deep hands-on experience with Apache Spark, Kafka, and the broader Apache ecosystem
• Proven success designing and supporting real-time data streams and batch workflows
• Solid experience with Airflow or equivalent orchestration tools
• Strong understanding of distributed systems, data architecture, and scalable design patterns
• Passion for clean, maintainable code and building robust, fault-tolerant systems

Nice to Have

• Experience with Delta Lake, Apache Iceberg, or Apache Hudi
• Familiarity with containerized workloads (Docker, Kubernetes, ECS/EKS)
• Background in building internal data platforms or centralized data lakes
• Experience supporting data science and BI/analytics teams

Knowledge of data privacy, compliance, and security practices (e.g., SOC 2, GDPR)

Details

• Payment in USD [2800-6000 USD]
• Full time