Sr. Software Engineer (Big Data, Data Lake)

Foureyes is a remote-first company focused on the automotive vertical, seeking a Sr. Software Engineer to design and implement their core data platform. The role involves building scalable data ingestion and integration across multiple data sources using AWS-native services, while collaborating with various teams to ensure data availability and performance.

Responsibilities:

• Strong leadership skills - you are comfortable both leading software engineers and rolling up your sleeves to implement and deploy the best solution
• Strong cross-functional collaboration with product, engineering, and analytics teams to ensure data availability, reliability, and performance
• Strong communication skills and experience translating business requirements into system design, architecture diagrams, and technical documentation
• Strong communication presenting complex concepts or solutions to diverse audiences through clear and concise written communication (e.g., report writing, email crafting) and effective verbal communication (e.g., presentations, stakeholder updates)
• Strong problem solving skills and knowledge of applied algorithms to solve real world problems efficiently
• You have operated in a team’s on-call rotation to address complex problems in real-time and keep services operational and highly available
• Strong hands-on experience implementing and using AWS data services: S3, Glue (ETL/Jobs, Data Catalog, DataBrew), Athena, Lake Formation, Step Functions, Lambda, Kinesis Data Stream and API Gateway
• Expertise in designing and optimizing data pipelines for high-volume, multi-source ingestion of structured and semi-structured data in a multi-tenant data architecture using different data lake formats (AWS S3Tables, Apache Iceberg, Apache Hudi, Apache Parquet)
• Experience with entity resolution, data cleansing, data quality, and anomaly detection
• Expert level skills developing back-end distributed systems and data pipelines using Python, Pyspark, SQL, Step Functions, Lambdas
• Comfort working with cloud data warehouses (Athena, Snowflake, Redshift, or similar)
• Experience building event-driven and notification systems (SNS/SQS, EventBridge, Pub/Sub, webhooks) and orchestration frameworks (StepFunctions or equivalent)
• Experience integrating AWS data pipelines with external platforms (e.g., Snowflake, Metabase, reporting tools, etc.)
• Hands on experience applying security best practices for data storage, transfer, and API access
• 7-10 years professional experience working in a software development environment, ideally with exposure to big data and data-rich applications
• Experience working across disciplines, partnering with BI, ML, and product teams to translate ideas into customer-facing features
• 5+ years working in an AWS cloud-native environment
• Prior experience in data-rich SaaS products
• Experience with auth & access control for data-driven applications in a multitenant environment
• Familiarity with data governance concepts (lineage, permissions, quality checks)
• Deployment experience (AWS CDK, CI/CD, containerized services, serverless functions)
• Exposure to generative AI or LLM-based data exploration tools

Requirements:

• Strong leadership skills - you are comfortable both leading software engineers and rolling up your sleeves to implement and deploy the best solution
• Strong cross-functional collaboration with product, engineering, and analytics teams to ensure data availability, reliability, and performance
• Strong communication skills and experience translating business requirements into system design, architecture diagrams, and technical documentation
• Strong communication presenting complex concepts or solutions to diverse audiences through clear and concise written communication (e.g., report writing, email crafting) and effective verbal communication (e.g., presentations, stakeholder updates)
• Strong problem solving skills and knowledge of applied algorithms to solve real world problems efficiently
• You have operated in a team's on-call rotation to address complex problems in real-time and keep services operational and highly available
• Strong hands-on experience implementing and using AWS data services: S3, Glue (ETL/Jobs, Data Catalog, DataBrew), Athena, Lake Formation, Step Functions, Lambda, Kinesis Data Stream and API Gateway
• Expertise in designing and optimizing data pipelines for high-volume, multi-source ingestion of structured and semi-structured data in a multi-tenant data architecture using different data lake formats (AWS S3Tables, Apache Iceberg, Apache Hudi, Apache Parquet)
• Experience with entity resolution, data cleansing, data quality, and anomaly detection
• Expert level skills developing back-end distributed systems and data pipelines using Python, Pyspark, SQL, Step Functions, Lambdas
• Comfort working with cloud data warehouses (Athena, Snowflake, Redshift, or similar)
• Experience building event-driven and notification systems (SNS/SQS, EventBridge, Pub/Sub, webhooks) and orchestration frameworks (StepFunctions or equivalent)
• Experience integrating AWS data pipelines with external platforms (e.g., Snowflake, Metabase, reporting tools, etc.)
• Hands on experience applying security best practices for data storage, transfer, and API access
• 7-10 years professional experience working in a software development environment, ideally with exposure to big data and data-rich applications
• Experience working across disciplines, partnering with BI, ML, and product teams to translate ideas into customer-facing features
• 5+ years working in an AWS cloud-native environment
• Prior experience in data-rich SaaS products
• Experience with auth & access control for data-driven applications in a multitenant environment
• Familiarity with data governance concepts (lineage, permissions, quality checks)
• Deployment experience (AWS CDK, CI/CD, containerized services, serverless functions)
• Exposure to generative AI or LLM-based data exploration tools