Design, build, and maintain ETL/ELT data pipelines and data lake solutions to support analytics and AI/ML use cases. Ensure data quality, performance, and reliability across enterprise data platforms.Key ResponsibilitiesPipeline DevelopmentData Lake EngineeringPerformance & OptimizationCollaboration & SupportRequired Skills & Experience 4+ years of experience in data engineering or ETL development. Proficiency in SQL and Python (or Scala/Java) for data transformations. Hands-on with ETL tools (Informatica, Talend, dbt, SSIS, Glue, or similar). Exposure to big data technologies (Hadoop, Spark, Hive, Delta Lake). Familiarity with cloud data platforms (AWS Glue/Redshift, Azure Data Factory/Synapse, GCP Dataflow/BigQuery). Understanding of workflow orchestration (Airflow, Oozie, Prefect, or Temporal).Preferred Knowledge Experience with real-time data pipelines using Kafka, Kinesis, or Pub/Sub. Basic understanding of data warehousing and dimensional modeling. Exposure to containerization and CI/CD pipelines for data engineering. Knowledge of data security practices (masking, encryption, RBAC).Education & Certifications Bachelors degree in Computer Science, IT, or related field.Preferred certifications:o AWS Data Analytics Specialty / Azure Data Engineer Associate / GCP Data Engineer.o dbt or Informatica/Talend certifications.