Senior Data Engineer

Tezo is a new generation Digital & AI solutions provider, with a history of creating remarkable outcomes for our customers. We bring exceptional experiences using cutting-edge analytics, data proficiency, technology, and digital excellence.

Sr Data Engineer – Azure & Snowflake

Location: Hyderabad

Experience Level: 8–13 Years

• 8+ years

  of experience in

  data engineering and ETL development

  .
• Strong proficiency in

  SQL

  (performance tuning, window functions, stored procedures).
• Hands-on experience with

  Azure Data Factory

  ,

  Azure Synapse

  ,

  Azure Data Lake

  , and

  Databricks

  .

• Snowflake

  expertise in data loading, transformations, and query optimization.
• Strong

  Python

  skills, including working with

  Pandas / PySpark dataframes

  in

  Jupyter notebooks

  .
• Experience with

  data orchestration

  ,

  workflow scheduling

  , and

  CI/CD for data pipelines

  .
• Good understanding of

  data modeling principles

  ,

  data governance

  , and

  metadata management

  .

Key Responsibilities

Data Engineering & Pipeline Development

• Design, build, and maintain

  scalable and reusable data pipelines

  for batch and real-time ingestion using

  Azure Data Factory

  ,

  Databricks

  , or

  PySpark

  .
• Develop and optimize

  ETL/ELT workflows

  to extract data from heterogeneous sources (files, APIs, databases, applications).
• Build and maintain data processing logic using

  Python, PySpark

  , and

  SQL

  .
• Work with

  dataframes

  in Jupyter notebooks for transformation, validation, and feature creation.

Data Architecture & Cloud Integration

• Implement and maintain

  data solutions on Azure and Snowflake

  .
• Design and manage data storage layers —

  staging, raw, curated, and consumption zones

  within

  Data Lake / Lakehouse

  architecture.
• Integrate structured and semi-structured data (JSON, Parquet, CSV, etc.) from multiple systems and sources.
• Collaborate with architects and modelers to align pipelines with

  data models and governance standards

  .

Performance Optimization & Data Quality

• Optimize pipelines for performance, scalability, and cost efficiency.
• Implement

  data validation, error handling, and audit mechanisms

  in ETL workflows.
• Participate in

  data profiling and quality assessments

  to ensure reliability and accuracy.

Collaboration & Stakeholder Engagement

• Work closely with

  data modelers, analysts, and business teams

  to translate functional requirements into technical solutions.
• Participate in

  code reviews

  ,

  architecture discussions

  , and

  Agile sprint ceremonies

  .
• Document processes, data flow diagrams, and technical designs.