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.