<h3>📋 Description</h3> • Lead the charge on a team responsible for developing the data architecture powering the data collection process and analytics platform
• Design/develop/extend data pipeline services and architecture to implement solutions on the data platform
• Foster team growth by mentoring junior engineers and evangelizing best practices
• Improve the quality of solutions and reliability of data across the organization
• Own projects from idea through production deployment
• Drive innovations within the team; collaborate on critical data initiatives
• Technologies used: SQL, Python; AWS, Docker, Kubernetes, Apache Airflow, Apache Spark, Apache Kafka, Terraform; Snowflake, Trino/Starburst, Redshift, MongoDB, Postgres, MySQL; Tableau <h3>🎯 Requirements</h3> • 10+ years of professional software engineering experience
• Strong proficiency with Python and SQL
• Strong proficiency with data processing technologies such as Spark, Flink, and Airflow
• Strong proficiency with RDMS/NoSQL/Big Data solutions (Postgres, MongoDB, Snowflake, etc.)
• Solid understanding of streaming solutions such as Kafka, Pulsar, Kinesis/Firehose, etc.
• Hands-on experience with Docker, Kubernetes, infrastructure as code using Terraform, and Kubernetes package management with Helm charts
• Solid understanding of ETL/ELT and OLTP/OLAP concepts
• Solid understanding of columnar/row-oriented data structures (e.g. Parquet, ORC, Avro, etc.)
• Solid understanding of Apache Iceberg, or other open table formats
• Proven ability to transform raw unstructured/semi-structured data into structured data in accordance to business requirements
• Solid understanding of AWS, Linux and infrastructure concepts
• Proven ability to diagnose and address data abnormalities in systems
• Proven ability to learn quickly, make pragmatic decisions, and adapt to changing business needs
• Experience building data warehouses using conformed dimensional models
• Experience building data lakes and/or leveraging data lake solutions (e.g. Trino, Dremio, Druid, etc.)
• Experience working with business intelligence solutions (e.g. Tableau, etc.)
• Experience working with ML/Agentic AI pipelines (e.g. , Langchain, LlamaIndex, etc.)
• Understands Domain Driven Design concepts and accompanying Microservice Architecture
• Passion for data, analytics, or machine learning.
• Focus on value: shipping software that matters to the company and the customer
• Bonus Points Experience working with vector databases
• Bonus Points Experience working within a retail or ecommerce environment.
• Bonus Points Proficiency in other programming languages such as Scala, Java, Golang, etc.
• Bonus Points Experience working with Apache Arrow and/or other in-memory columnar data technologies