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Job Summary:
Seeking an experienced Senior Data Engineer to lead data ingestion, transformation, and optimization initiatives using the modern Apache and Azure data stack. The role involves working on scalable pipelines, large-scale distributed systems, and data lake management.
Core Responsibilities:
· Build and manage high-volume data pipelines using Spark/Databricks.
· Implement ELT frameworks using Azure Data Factory/Synapse Pipelines.
· Optimize large-scale datasets in Delta/Iceberg formats.
· Implement robust data quality, monitoring, and governance layers.
· Collaborate with Data Scientists, Analysts, and Business stakeholders.
Technical Stack:
· Big Data: Apache Spark, Kafka, Hive, Airflow, Hudi/Iceberg
· Cloud: Azure (Synapse, ADF, ADLS Gen2), Databricks, AWS (Glue/S3)
· Languages: Python, Scala, SQL
· Storage Formats: Delta Lake, Iceberg, Parquet, ORC
· CI/CD: Azure DevOps, Terraform (infra as code), Git
Senior Data Engineer (Apache Stack + Databricks/Synapse)
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Thirega@ vysystems dot com - WhatsApp - 91Five0033Five2Three
- 5+ years of experience in a Data Engineering role on cloud environment
- Must have good experience in Scala/PySpark (preferably on data-bricks environment)
- Extensive experience with Transact-SQL.
- Experience in Data-bricks/Spark.
- Strong experience in Dataware house projects
- Expertise in database development projects with ETL processes.
- Manage and maintain data engineering pipelines
- Develop batch processing, streaming and integration solutions
- Experienced in building and operationalizing large-scale enterprise data solutions and applications
- Using one or more of Azure data and analytics services in combination with custom solutions
- Azure Data Lake, Azure SQL DW (Synapse), and SQL Database products or equivalent products from other cloud services providers
- In-depth understanding of data management (e. g. permissions, security, and monitoring).
- Cloud repositories for e.g. Azure GitHub, Git
- Experience in an agile environment (Prefer Azure DevOps).
Good to have
- Manage source data access security
- Automate Azure Data Factory pipelines
- Continuous Integration/Continuous deployment (CICD) pipelines, Source Repositories
- Experience in implementing and maintaining CICD pipelines
- Power BI understanding, Delta Lake house architecture
- Knowledge of software development best practices.
- Excellent analytical and organization skills.
- Effective working in a team as well as working independently.
- Strong written and verbal communication skills.
- Expertise in database development projects and ETL processes.
- Building and operationalizing large scale enterprise data solutions and applications using one or more of AZURE data and analytics services in combination with custom solutions - Azure Synapse/Azure SQL DWH, Azure Data Lake, Azure Blob Storage, Spark, HDInsights, Databricks, CosmosDB, EventHub/IOTHub.
- Experience in migrating on-premise data warehouses to data platforms on AZURE cloud.
- Designing and implementing data engineering, ingestion, and transformation functions
- Experience with Azure Analysis Services
- Experience in Power BI
- Experience with third-party solutions like Attunity/Stream sets, Informatica
- Experience with PreSales activities (Responding to RFPs, Executing Quick POCs)
- Capacity Planning and Performance Tuning on Azure Stack and Spark.


