Data Product Engineer

Job Description

Data Product Engineer Job 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.Key Responsibilities.

●      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.

Requirements

●      Experience: 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.

●      Cloud Proficiency: 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).

●      Programming & Scripting: Expert-level proficiency in Advanced SQL (T-SQL, PL/SQL) and Python/PySpark for data manipulation and engineering tasks.

●      Data Tools: Proven expertise with ETL/ELT tools (e.g., SSIS, ADF, Informatica) and data governance/modeling tools (e.g., dbt, Erwin Data Modeler).

●      BI Tools: Strong ability to design and optimize reports, dashboards, and semantic models using tools like Power BI, Tableau, or QuickSight.

●      Soft Skills: Exceptional communication, technical documentation, and stakeholder management skills to translate between technical and business teams.