Job Role: Data Engineer

POSITION OVERVIEW

DUTIES AND RESPONSIBILITIES

• Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, standardize, and process data from multiple sources.
• Write efficient SQL queries and develop data processing solutions using Python, Scala, Java, or other relevant programming languages.
• Implement data validation, quality checks, monitoring, and error-handling mechanisms to ensure data accuracy and reliability.
• Integrate data from external systems, partner platforms, APIs, and structured or semi-structured data sources.
• Work with cloud and data platforms such as Snowflake, Databricks, and AWS to build and maintain data processing workflows.
• Support data modeling, transformation, and preparation activities to make data available for analytics, reporting, and machine learning use cases.
• Identify and troubleshoot data pipeline failures, performance bottlenecks, and data inconsistencies.
• Follow data security, privacy, access control, and governance practices while handling sensitive or business-critical data.
• Collaborate with Data Engineers, Data Scientists, and other stakeholders to understand requirements and deliver reliable data solutions.
• Maintain technical documentation, pipeline specifications, operational runbooks, and data lineage information.
• Use orchestration tools and, where applicable, streaming technologies to automate and manage data workflows.
• Explore AI-assisted development tools to improve productivity while validating generated code for accuracy, security, and maintainability.

QUALIFICATIONS

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 2+ years of hands-on experience in Data Engineering, ETL/ELT development, or a related data-focused role.
• Strong proficiency in SQL, including complex queries, joins, aggregations, and query optimization.
• Hands-on experience with at least one programming language, preferably Python, Scala, or Java.
• Experience developing, maintaining, or troubleshooting ETL/ELT data pipelines.
• Familiarity with cloud platforms and modern data technologies such as Snowflake, Databricks, or AWS.
• Understanding of data modeling, data transformation, data quality, and pipeline monitoring.
• Basic knowledge of data security, privacy, and governance practices.
• Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Exposure to identity resolution, entity matching, record linkage, graph-based data processing, or graph databases.
• Experience in integrating external data sources through APIs, partner feeds, or third-party platforms.
• Familiarity with workflow orchestration tools such as Apache Airflow or similar technologies.
• Exposure to streaming and event-processing technologies such as Apache Kafka or AWS Kinesis.
• Familiarity with data clean rooms, privacy-preserving data processing, or consent-based data handling.
• Experience working in data-driven product environments, preferably in AdTech, MarTech, or digital analytics.
• Exposure to full-stack development, including front-end and back-end technologies, beyond core data engineering.
• Familiarity with LLMs, RAG, MCP, and AI-assisted development tools such as GitHub Copilot or Claude Code.
• Understanding of best practices for validating AI-generated code and using AI-assisted development workflows responsibly.