Lead Data Engineer Needed
Budget: $25 – $50 USD
Staff Data Engineeer
• Data Engineering Leadership: You are responsible for bridging technical gaps to lead and oversee various data engineering projects for our data solutions engagements.
• Cross-Team Collaboration: You are responsible for contributing to alignment across the organization through influence and by translating context across different teams.
• Project Enablement: You are responsible for ensuring that large and/or more complex engineering projects are delivered in alignment with the appropriate business outcomes.
• Proven experience as a Data Engineer or related role, with a focus on designing and developing data pipelines.
• Strong programming skills in Python and SQL. Experience with Scala and Rust is a plus but not required.
• Deep knowledge of data warehousing and ETL/ELT processes.
• Intermediate / expert proficiency with common data integration / orchestration platforms (e.g., Fivetran, Azure Data Factory, Apache Airflow)
• Deep experience with at least one cloud data warehouse (Snowflake, BigQuery, Databricks, or similar).
• Experience with streaming solutions such as Spark Streaming, Kafka, or Flink is desirable but not required.
• Strong experience with at least one cloud platform such as AWS, Azure, or Google Cloud.
• Experience mentoring and advising other engineers
• Ability to define, explain, and sell long-term vision for technical architecture, technical approaches / procedures, etc.
• Excellent communication and collaboration skills.
• Data Engineering Leadership: You are responsible for bridging technical gaps to lead and oversee various data engineering projects for our data solutions engagements.
• Cross-Team Collaboration: You are responsible for contributing to alignment across the organization through influence and by translating context across different teams.
• Project Enablement: You are responsible for ensuring that large and/or more complex engineering projects are delivered in alignment with the appropriate business outcomes.
• Proven experience as a Data Engineer or related role, with a focus on designing and developing data pipelines.
• Strong programming skills in Python and SQL. Experience with Scala and Rust is a plus but not required.
• Deep knowledge of data warehousing and ETL/ELT processes.
• Intermediate / expert proficiency with common data integration / orchestration platforms (e.g., Fivetran, Azure Data Factory, Apache Airflow)
• Deep experience with at least one cloud data warehouse (Snowflake, BigQuery, Databricks, or similar).
• Experience with streaming solutions such as Spark Streaming, Kafka, or Flink is desirable but not required.
• Strong experience with at least one cloud platform such as AWS, Azure, or Google Cloud.
• Experience mentoring and advising other engineers
• Ability to define, explain, and sell long-term vision for technical architecture, technical approaches / procedures, etc.
• Excellent communication and collaboration skills.