About this role
Full Time Mid-level Data Engineer in AI at Virtusa in IN-AP-Hyderabad. Apply directly through the link below.
At a glance
- Work mode
- Office
- Employment
- Full Time
- Location
- IN-AP-Hyderabad
- Experience
- Mid-level · 5+ years
Core stack
- Data Engineering
- Distributed
- Databricks
- Snowflake
- Analytics
- Incident
- Python
- Design
- Azure
- CI/CD
- Spark
- SOLID
- SQL
- ETL
- Git
Quick answers
What are the qualifications?
Bachelor’s/master’s degree in Comp Science, Data Analytics, Engineering,
What skills are required?
Data Engineering, Distributed, Databricks, Snowflake, Analytics, Incident, Python, Design, Azure, CI/CD, and more.
Virtusa is hiring for this role. Visit career page
Hyderābād, India
Description
Key Responsibilities
The following are the key responsibilities of the position. It is expected
that most, if not all of these, are met by the candidate:
Design, build, and optimize data pipelines using Azure Data Factory and
Databricks (pyspark/spark SQL).
Develop robust ETL/ELT processes to ingest, transform, and validate large
volumes of operational, telemetry, incident, and transactional data.
Implement scalable workflows leveraging Azure services such as Data Lake
Storage, SQL Databases, Key Vault, Logic Apps, and Functions.
Develop clean, maintainable, and well-documented Python code for data
processing, automation, and model-serving pipelines.
Build efficient SQL queries and stored procedures across Oracle and SQL
Server to support the ODS, EDW, and analytics layer.
Contribute to data engineering standards, best practices, reusable
templates, and version control via Git.
Required Skills and Qualifications
Bachelor’s/master’s degree in Comp Science, Data Analytics, Engineering,
Mathematics, or related field.
5+ years of experience in data engineering roles.
Strong expertise with Azure Data Factory (ADF) pipelines, triggers, mapping
data flows, and orchestrations.
Advanced experience with Azure Databricks (pyspark, spark SQL, Delta Lake,
notebooks, clusters).
High proficiency in Python for ETL, automation, and data transformation.
Strong SQL skills across Oracle and SQL Server, including query tuning and
complex transformations.
Solid understanding of data modelling, warehousing, star/snowflake schema,
and distributed data processing.
Experience handling large-scale datasets and complex data domains.
Familiarity with CI/CD practices, Git branching, and DevOps pipelines.
Experience with data governance, data cataloging, and managing
structured/unstructured data in cloud environments.