Data Engineer

Tezo

Role : Data Engineer

Location: Hyderabad

Experience Level: =4-8 Years

• 4+ years

  of experience in

  Data Engineering / ETL development

  .
• Strong

  SQL

  skills (advanced joins, window functions, query optimization).
• Hands-on experience with

  Azure Data Factory, Azure Synapse, and Azure Data Lake

  .
• Strong experience in

  Python

  for data manipulation, transformation, and automation (Pandas / PySpark preferred).
• Experience integrating and processing data from

  multiple source systems

  (files, APIs, databases, etc.).
• Good understanding of

  data modeling principles

  and

  ETL best practices

  .
• Strong communication skills and ability to work effectively in Agile delivery teams.

Key Responsibilities

ETL & Data Pipeline Development

• Design, build, and deploy

  ETL/ELT workflows

  for ingesting, transforming, and loading data from multiple source systems into data warehouses or data lakes.
• Develop

  Python-based ETL scripts

  and reusable data processing frameworks.
• Implement

  data ingestion pipelines

  using

  Azure Data Factory

  ,

  Data Lake

  , and

  Databricks

  .
• Work with both

  batch and incremental data loads

  , ensuring data consistency and reliability.

Data Engineering & Cloud Implementation

• Develop and maintain

  data pipelines on Azure Cloud

  , integrating data across on-prem and cloud environments.
• Work with

  Azure Data Lake, Synapse Analytics, SQL Database

  , and

  Azure Data Factory (ADF)

  to deliver scalable solutions.
• Participate in designing

  data architecture layers

  raw, curated, and consumption zones.
• Work with

  structured and semi-structured data

  (CSV, JSON, Parquet, XML).

Data Quality, Performance & Optimization

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

  data quality, validation, and error-handling mechanisms

  across ETL processes.
• Ensure best practices in

  data security

  ,

  governance

  , and

  metadata management

  .

Collaboration & Delivery

• Collaborate with

  data modelers, business analysts, and architects

  to translate business requirements into robust data engineering solutions.
• Participate in

  Agile ceremonies

  , peer code reviews, and sprint planning.
• Prepare and maintain technical documentation for all ETL processes and data flows.