What are the responsibilities and job description for the Principal Data Engineer position at HireStarter, Inc.?
HireStarter's client is a consumer marketing technology company. They specialize in building and operating a diverse network of consumer-facing websites. Their expertise lies in creating effective connections between consumers and advertisers across multiple verticals such as job opportunities, educational resources, and clinical trials. They are a rapidly growing firm looking for an enthusiastic and talented individual who thrives on having a lot of responsibility.
As a Principal Data Engineer, you will play a key leadership role in designing, architecting, and implementing data systems consuming over a billion rows of data a month, to power real-time insights for the business operations team. You will define the data architecture, tooling, and best practices that enable efficient data processing, storage, and analysis.
Responsibilities
Architectural Leadership - Lead the design and implementation of scalable data architectures and frameworks.
Data Pipeline Development : Oversee the development of efficient data pipelines to ensure timely and reliable data delivery.
Data Transformation : Utilize DBT to create and manage data transformation processes.
Dimensional Model Design : Design and build a robust reporting layer above replicated data that provides actionable insights for business users.
Cross-Functional Collaboration : Work closely with data scientists, analysts, and other stakeholders to understand their data needs and how best to structure and deliver that data.
Data Governance and Compliance : Ensure compliance with data governance standards and regulatory requirements, while also advocating for data security practices across data engineering initiatives.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, or related field.
- 8 years of experience in data engineering, with a focus on high-scale data processing.
- Proven track record of designing and implementing large-scale data solutions in Snowflake and other data warehousing environments.
- Exceptional proficiency in SQL and experience with analytical databases and tools.
- Strong experience with data pipeline orchestration tools (e.g., Airflow, dbt, Prefect).
- Deep understanding of cloud-based data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).
- Experience with real-time data processing frameworks (e.g., Kafka, Flink, Spark Streaming).
- Strong knowledge of database performance optimization and query tuning.
- Experience working in a fast-paced, high-growth environment with large data volumes.
Benefits
No-cost, fully paid medical / dental / vision benefits, unlimited PTO, employee profit sharing, 401(k) with 3% employer contribution (no matching required), among others.