Data Engineer

About the Role

We are seeking a skilled Data Engineer with 3+ years of professional experience to join our engineering team and support a digital research and focus-group platform where participants complete surveys through web and mobile experiences, and research data is collected, processed, and prepared for analysis.

The ideal candidate will have strong hands-on experience with Python, SQL, ETL/ELT pipelines, data warehousing, and cloud platforms. You will be responsible for building scalable and reliable data pipelines, transforming large volumes of survey and participant data, and ensuring the accuracy, quality, privacy, and accessibility of data used by research, analytical, and business teams.

Key Responsibilities

• Design and maintain the data architecture supporting the Research platform
• Build pipelines for survey responses, participant activity, research studies, incentives/rewards and application events
• Transform raw survey and participant data into structured datasets for reporting and analysis
• Develop scalable pipelines to support research and analytical workloads
• Create clean data models for respondent, survey, question, response and study-level analytics
• Build aggregation pipelines for dashboards and research reporting
• Integrate data from internal services, APIs and third-party systems
• Implement data quality checks, monitoring and alerting
• Optimize database queries and data-processing performance
• Maintain historical and audit-ready datasets
• Support data exports required by research and business teams
• Work closely with backend engineers, analysts, researchers and product teams
• Ensure appropriate data privacy, security and access controls, particularly because the platform handles confidential research responses.

Requirements

• 3+ years of hands-on Data Engineering experience
• Strong proficiency in Python and SQL
• Experience designing and maintaining scalable ETL/ELT pipelines
• Experience working with large volumes of transactional, survey, event and analytical data
• Strong knowledge of relational databases such as PostgreSQL / MySQL
• Experience with data warehouses such as Snowflake, BigQuery, Redshift, Azure Synapse or similar
• Experience with cloud environments such as AWS, Azure or GCP
• Understanding of data modelling, normalization and dimensional modelling
• Experience building reliable batch and/or real-time data pipelines
• Strong knowledge of data validation, data quality and reconciliation
• Experience integrating data from APIs and third-party platforms
• Familiarity with Git, CI/CD, Docker and modern engineering practices
• Strong analytical and troubleshooting skills