Jobs → Data & Analytics → Data Engineer

About the Role We are looking for an experienced Data Engineer to design, develop, and maintain scalable data pipelines and enterprise data solutions. The ideal candidate should have strong hands-on experience in Python, SQL, ETL/ELT processes, data warehousing, and cloud-based data platforms. Key Responsibilities • Design, develop, and maintain scalable data pipelines for extracting, transforming, and loading data from multiple sources • Build and optimize ETL/ELT workflows to process structured, semi-structured, and unstructured data • Develop data processing applications and transformation logic using Python, PySpark, and SQL • Work with Apache Spark and distributed processing frameworks to handle large volumes of enterprise data • Develop batch and real-time data processing pipelines for analytics and reporting requirements • Build and maintain data lakes, data warehouses, and lakehouse solutions • Integrate data from relational databases, APIs, cloud storage, and enterprise applications • Perform data cleansing, validation, transformation, and reconciliation to maintain data accuracy • Develop and optimize complex SQL queries, stored procedures, and database operations • Work with cloud data platforms and services across AWS, Microsoft Azure, or Google Cloud Platform • Develop and manage data workflows using Databricks, AWS Glue, Azure Data Factory, or similar platforms • Implement data modeling, partitioning, indexing, and performance optimization techniques • Monitor data pipelines, troubleshoot failures, and resolve production data processing issues • Automate workflow scheduling and orchestration using Apache Airflow or similar tools Requirements • 6+ years of experience as a Data Engineer • Strong hands-on experience in Python, PySpark, and SQL • Experience with ETL/ELT processes and data warehousing • Knowledge of cloud-based data platforms (AWS, Azure, GCP) • Experience with big data technologies (Apache Spark, Hadoop, Hive, Kafka) • Familiarity with data platforms (Databricks, Snowflake, Amazon Redshift, Azure Synapse Analytics) • Experience with databases (Oracle, SQL Server, PostgreSQL, MySQL) • Understanding of data architecture concepts (Data Warehousing, Data Lakes, Lakehouse, Data Modeling)