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Posted 2d ago

DE&A - Core - Cloud Data Engineering - Snowflake Data Engineering

@ Zensar
Pune, Maharashtra, India
OnsiteFull Time
Responsibilities:designing pipelines, building ETL, mentoring engineers
Requirements Summary:8+ years IT experience with 5+ years in data engineering, strong SQL and Python, experience designing data pipelines, ETL/ELT, data warehousing, cloud data platforms (Azure preferred), and big data technologies.
Technical Tools Mentioned:Microsoft Azure Data Factory (ADF), Microsoft Azure Synapse Analytics, Microsoft Azure Data Lake Storage (ADLS), Microsoft Azure Databricks, Microsoft Fabric, Glue, Redshift, EMR, S3, BigQuery, Dataflow, Cloud Storage, Apache Spark, Databricks, Hadoop Ecosystem, Kafka, Delta Lake, Microsoft SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, Microsoft Azure SQL Database, Python, SQL, PySpark, Scala, Shell Scripting, Microsoft Azure DevOps, Git, CI/CD Pipelines, Jenkins
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Job Description

We are seeking a highly skilled Senior Data Engineer with 8–12 years of experience in designing, developing, and managing scalable data platforms and enterprise data solutions. The ideal candidate will have strong expertise in data engineering, cloud technologies, ETL/ELT development, data warehousing, and big data ecosystems.

The candidate will play a key role in building modern data platforms, enabling advanced analytics, business intelligence, AI/ML initiatives, and data-driven decision-making across the organization.

Responsibilities

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and data integration frameworks.
  • Build and optimize ETL/ELT processes for structured and unstructured data sources.
  • Develop and manage enterprise data warehouses, data lakes, and lakehouse architectures.
  • Implement data ingestion, transformation, and orchestration solutions using cloud-native services.
  • Collaborate with business analysts, data scientists, architects, and stakeholders to understand data requirements.
  • Ensure data quality, governance, security, and compliance standards are met.
  • Optimize database and query performance for large-scale datasets.
  • Design and implement real-time and batch data processing solutions.
  • Support reporting, analytics, AI/ML, and advanced data engineering initiatives.
  • Participate in architecture reviews and provide technical leadership to the data engineering team.
  • Develop CI/CD pipelines and automate deployment processes for data platforms.
  • Mentor junior engineers and establish engineering best practices.