[Hiring] Data Product Engineer @ETHICS CODE

Role Description

We are seeking an experienced and highly motivated Data Product Engineer to bridge the gap between engineering and product management. This role involves owning the end-to-end lifecycle of our data products, from strategic conception and requirement gathering to technical implementation, quality assurance, and adoption. The ideal candidate will leverage a strong background in scalable data engineering, cloud architecture, and business intelligence to transform complex business problems into reliable, high-value data assets and actionable insights.

• Product Strategy & Roadmap: Partner with Product Managers, Business Analysts, and key stakeholders (Finance, Operations) to define the vision, strategy, and roadmap for critical data products.
• Requirements & Design: Translate high-level business objectives and user needs into detailed, clear, and actionable data requirements, architecture, and technical designs for data products.
• Data Pipeline Development: Design, build, and maintain highly scalable and reliable ETL/ELT data pipelines using modern cloud tools (e.g., Azure Data Factory, AWS Glue, Databricks, PySpark) to integrate diverse data sources.
• Data Modeling & Warehousing: Develop and optimize performant data models (Star/Snowflake schema) in cloud data warehouses (e.g., Snowflake, BigQuery, Synapse) with a focus on data quality, governance, and compliance.
• Quality & Governance: Implement data quality checks, data lineage tracking (e.g., dbt), and robust testing to ensure the accuracy and trustworthiness of all delivered data products.
• Visualization & Adoption: Lead the delivery of BI solutions (e.g., Power BI, Tableau), ensuring dashboards and reports are intuitive, accurate, and drive measurable business decisions.
• Deployment & Operations: Utilize Agile methodologies and CI/CD practices (e.g., GitHub, Azure DevOps, Jenkins) to deploy, monitor, and optimize data products, ensuring high availability and cost efficiency.
• Mentorship & Collaboration: Act as a technical leader, mentoring junior team members and fostering a culture of data-as-a-product within the organization.

Qualifications

• Minimum of 5+ years of experience in Data Engineering, Business Intelligence, or a related field, with 2+ years focused on the product lifecycle of data assets.
• Deep hands-on experience with at least one major cloud platform (Azure, AWS, or GCP) and its native data services (e.g., ADF, Synapse, Databricks, Redshift, BigQuery).
• Expert-level proficiency in Advanced SQL (T-SQL, PL/SQL) and Python/PySpark for data manipulation and engineering tasks.
• Proven expertise with ETL/ELT tools (e.g., SSIS, ADF, Informatica) and data governance/modeling tools (e.g., dbt, Erwin Data Modeler).
• Strong ability to design and optimize reports, dashboards, and semantic models using tools like Power BI, Tableau, or QuickSight.
• Exceptional communication, technical documentation, and stakeholder management skills to translate between technical and business teams.