Data Engineer

<div>About the Role</div><div>We are looking for a Software Engineer – Data Engineering to design, build, and maintain robust, scalable, and high-performance data infrastructure. In this role, you will work on end-to-end data pipelines, ensuring reliable data availability for analytics, machine learning, and business applications. </div><div><br /></div><div>Key Responsibilities</div><div>Data Pipeline Development:</div><div>Design, implement, and optimize ETL/ELT pipelines for structured and unstructured data.</div><div>Integrate data from multiple internal and external sources into centralized systems.</div><div>Build scalable batch and real-time data processing workflows.</div><div><br /></div><div>Data Infrastructure & Architecture:</div><div>Develop and maintain data lake, data warehouse, or data mesh architectures.</div><div>Ensure high availability, performance, and scalability of data systems.</div><div>Implement data modeling best practices to support analytics and ML use cases.</div><div><br /></div><div>Software Engineering:</div><div>Write clean, efficient, and maintainable code in Python, Java, or Scala.</div><div>Implement unit tests, integration tests, and CI/CD pipelines for data workflows.</div><div>Apply software engineering principles to build reusable data services and APIs.</div><div><br /></div><div>Data Quality & Governance:</div><div>Implement validation, monitoring, and observability to ensure data accuracy and reliability.</div><div>Enforce data security, compliance, and privacy standards (e.g., GDPR).</div><div>Collaborate with stakeholders to establish data definitions, lineage, and documentation.</div><div><br /></div><div>Requirements</div><div>Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.</div><div>2–4 years of experience in data engineering, software engineering, or backend systems.</div><div>Strong programming skills in Python, Java, or Scala.</div><div>Experience with distributed data processing frameworks (Apache Spark, Flink, Beam, or similar).</div><div>Proficiency with SQL and relational databases; familiarity with NoSQL systems (Cassandra, MongoDB, DynamoDB).</div><div>Hands-on experience with cloud platforms (AWS, GCP, Azure) and data services (e.g., Redshift, BigQuery, Snowflake, Databricks).</div><div>Familiarity with workflow orchestration tools (Airflow, Luigi, Dagster) and CI/CD pipelines.</div><div>Solid understanding of software engineering best practices (version control, testing, code reviews).</div>