Data Engineer

Role Overview We are seeking a Data Engineer to design, build, and optimize scalable data pipelines and distributed data systems. This role involves working with large datasets, real-time and batch processing systems, and production-grade data infrastructure. You will be responsible for transforming raw data into reliable, structured, and high-quality datasets that power analytics, machine learning, and operational systems. Key Responsibilities • Design and implement scalable ETL/ELT pipelines • Build reliable batch and real-time data processing workflows • Develop data ingestion systems from multiple sources (APIs, streaming, files, databases) • Ensure data quality, validation, and monitoring • Optimize data storage, query performance, and cost efficiency • Design data models and schemas for analytical and operational use cases • Maintain data warehouse and/or data lake environments • Collaborate with backend, ML, and analytics teams Required Skills • Strong proficiency in Python and/or Java • Solid SQL skills and experience with relational databases • Experience building production-grade data pipelines • Understanding of distributed data processing concepts • Experience with data warehousing and data modeling • Familiarity with version control and CI/CD practices • Strong debugging and performance optimization skills Preferred Qualifications • Experience with big data tools (Spark, Hadoop, etc.) • Experience with streaming systems (Kafka, Kinesis, etc.) • Experience with cloud platforms (AWS / GCP / Azure) • Experience with data lakes and modern warehouse platforms • Exposure to ML data pipelines or feature engineering workflows • Knowledge of data governance and data quality frameworks