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India
Remote only
Understanding the business requirements
Writing code and implementing the proposed solutions
Creating data pipelines, versioning and change management
Manage the complexity inherent in versioned data pipelines
Develop ETL/ELT processes to help extract and manipulate data from multiple sources.
Design, build and maintain batch or real-time data pipelines in production.
Automate data workflows such as data ingestion, aggregation, and ETL processing.
Logging and instrumentation of pipelines and services.
Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures.
Train and mentor junior engineers.
Demonstrated expertise with a minimum of 5+ years of experience as data engineer or similar role
Advanced SQL skills and experience with relational databases and database design.
Experience working with cloud Data Warehouse solutions (e.g., Snowflake, Redshift, BigQuery, Azure Synapse, etc.).
Strong Python skills with hands-on experience on Pandas, NumPy and other data related libraries
Experience with Big Data technologies like Spark, Map Reduce, Hadoop, Hive etc
Proficiencient in data pipeline and workflow management tools e.g. Airflow
Experience with data visualization tools like PowerBI, Tableau, AWS QuickSight etc
Experience with the AWS/Azure/GCP data engineering services
Knowledge of AWS services viz., S3, Lambda, EMR, GLUE ETL, Athena, RDS, Redshift, EC2, IAM
OR
Knowledge of Azure services viz., ADF, Azure Synapse Analytics, ADLS Gen2, Azure SQL DB
Very good exposure of working on Data Lakes & Data Warehouses solutions
Excellent problem-solving, communication, and organizational skills.
Proven ability to work independently and with a team.
Ability to guide other data engineers.
Experience working with data ingestion tools such as Fivetran, stitch, or Matillion.
Good understanding of NoSQL databases like Redis, Cassandra, MongoDB, or Neo4j.
Familiarity with machine learning technologies.
Experience in Java or Scala