
Senior Data Engineer
1 week ago
Role- Data Engineer
Exp – 6yrs – 8yrs
Location- All GL Location
- Extensive hands-on experience implementing data migration and data processing using AWS services: S3 Data Lake, AWS Glue, Lambda Functions, Athena, RDS Aurora, Databricks.
- Good understanding of Data Governance, Data Security, Data Compliance, Data Quality, Metadata Management, Master Data Management, Data Catalog.
- Strong experience with data modeling and schema design.
- Strong SQL programming background.
- At least 6+years of consulting or client service delivery experience on AWS.
- At least 6+years of experience in developing data ingestion, data processing, and analytical pipelines for big data, relational databases, NoSQL, and data warehouse solutions.
- Well versed in DevSecOps and CI/CD deployments.
- Cloud migration methodologies and processes including tools like AWS Glue, Data Migration Service, Attunity (Qlik), Event Hub, Kafka, etc.
- Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage.
- Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing, and curation: Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
- Well versed in SQL Server and SSIS.
- Good to have Node JS, Python, .Net.
- Excellent interpersonal and teamwork skills.
- Good knowledge of Agile Scrum.
- Good communication skills.
- Experience implementing data integration patterns that support a Data Fabric architecture, such as API-based access and data virtualization.
- Hands-on experience with tools for metadata management and data lineage that enable a Data Fabric (e.g., Collibra, Informatica, Alation).
- Ability to build data pipelines that feed into a distributed data environment, ensuring data is discoverable and accessible to data consumers via the fabric.
Required Skills & Qualifications
- For Lead Data Engineer -> 8 to 10 years of experience in a Data Engineering role.
- For Data Engineer -> 6-8 years of experience in a Data Engineering role.
- Proven expertise with Microsoft Azure data services, including Azure Data Factory (ADF), Azure Data Lake Storage (ADLS) Gen2, and Azure Synapse or Databricks.
- Strong proficiency in Apache Spark (PySpark/Scala) and SQL, Data Fabric
- Experience with real-time data ingestion using services like Azure Event Hubs or Kafka.
- Familiarity with building CI/CD pipelines and using version control systems (Git).
Preferred/Good-to-Have
- Experience with schema registry and data governance tools like Azure Purview.
- Knowledge of microservices and event-driven architecture patterns.
- Experience with Infrastructure as Code (IaC) using Terraform or Bicep.
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