Job Description



Job Description


1. Role Overview


We are looking for a Data Engineer to design, develop, and optimize scalable data pipelines and storage systems. The candidate will work closely with analytics, product, and engineering teams to ensure high-quality data availability for business intelligence and ML workloads.



2. Key Responsibilities


A. Data Pipeline Development




  • Build and maintain batch & real-time ETL/ELT pipelines.




  • Integrate data from multiple sources (APIs, databases, cloud storage, streaming platforms).




  • Implement data transformation and cleansing logic.




B. Data Architecture & Modeling




  • Design data lakes, data warehouses, and data marts.




  • Build optimized schemas following normalization/denormalization standards.




  • Maintain high data availability and consistency across systems.




C. Cloud & Big Data Technologies




  • Work with cloud ecosystems (AWS, Azure, or GCP).




  • Use services such as S3, Redshift, BigQuery, Azure Data Factory, Databricks, EMR, etc.




  • Manage distributed frameworks (Spark, Kafka, Hadoop).




D. Performance & Reliability




  • Monitor pipeline performance and optimize resource usage.




  • Implement logging, monitoring, and error-handling mechanisms.




  • Automate pipeline deployments using CI/CD workflows.





3. Qualifications


Required Skills




  • Strong Python or Scala programming.




  • Experience with SQL, ETL tools, and cloud services.




  • Understanding of data structures, distributed computing, and pipeline orchestration (Airflow/Luigi).




Preferred Skills




  • Experience with dbt, Terraform, or containerization (Docker/K8s).




  • Knowledge of machine learning pipelines.





4. Salary Range




  • 6 LPA – 18 LPA (India), depending on experience.




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