Data Engineer II

Hagerty is a company built by drivers for drivers, serving automotive enthusiasts through insurance, membership, marketplace, events, and media. The Data Engineer II will build and maintain data pipelines, services, and cloud-based infrastructure supporting the Enterprise Data Hub, analytics, data products, and Hagerty’s Insurance business. The role also partners with engineers, stakeholders, data quality engineers, and data scientists to deliver scalable, governed, and reliable data solutions.

Responsibilities:

• Implement best practices around software development and big data engineering
• Develop and implement robust and scalable data pipelines using Python, SQL, parallel processing frameworks, and other AWS/Salesforce cloud solutions
• Develop and implement batch data pipelines using tools such as Apache Airflow, Snowflake, and numerous AWS products (EC2, Fargate, ECS, Lambda, and RDS)
• Develop streaming data integrations to support products across the Hagerty portfolio and support real-time reporting
• Develop Enterprise Data Hub platform infrastructure using Terraform infrastructure-as-code
• Develop and support Hagerty’s cloud-based data warehouse to enable analytics and product reporting
• Partner with internal and external stakeholders to collect requirements, recommend best practice solutions, and productionize new data ingestions/analytic workloads
• Develop solutions to catalog and manage metadata to support data governance and data democratization
• Partner with Data Quality Engineers to define and implement automated test cases and data reconciliation to validate ETL processes and data quality & integrity
• Mentor junior team members in software and big data engineering best practices
• Partner with Data Scientists to design, code, train, test, deploy and iterate machine learning algorithms and systems at scale

Requirements:

• You have strong problem-solving abilities and attention to detail
• You can authentically and effectively communicate (written and verbally) with various stakeholders
• You create and share technical artifacts and documentation to support development and maintenance of data products
• You have experience in successful delivery of data products as productionizable software solutions
• You ensure quality through rigorous code development, testing, automation, and other software engineering best practices
• You have experience developing solutions using Python and cloud-based infrastructure (AWS, Azure, or GCP)
• You demonstrate experience in imperative (e.g., Apache Airflow / NiFi) or declarative (e.g., Informatica/Talend/Pentaho) ETL design, implementation, and maintenance
• You have functional knowledge of relational databases and query authoring (SQL)
• Additional 3+ years working in another role within an IT delivery team, such as a developer, engineer, data analyst, quality assurance analyst, ETL developer or DBA
• Experience cataloging and processing non-relational data
• Experience with open-source data processing technologies such as streaming services (Kafka / SQS), big data processing frameworks (MapReduce/Spark), big data file stores (EMRFS / HDFS)
• Experience working with evaluating different data containers based on workload needs (JSON, delimited files, Avro, Parquet)
• Experience with container-based development
• This position is open to U.S. remote work. However, team members who reside within 20 miles of the Traverse City headquarters will follow a hybrid schedule, working from the office three days per week
• May require travel for quarterly events
• Familiarity with public company requirements, including Sarbanes Oxley and key regulations, if applicable
• Associates degree, preferably in a technical/analytical field, or relevant work experience
• Developing infrastructure as code in a cloud-based environment (Terraform experience preferred)