Sr. Data Engineer - PySpark, ETL, SQL

Aligned Automation Based in Pune,
Maharashtra, India office.

About the job

A
‘Better Together’ philosophy towards building a better world

Aligned Automation is a
strategic service provider that partners with Fortune 500 leaders to digitize
enterprise operations and enable business strategies. We believe we can create
positive, lasting change in the way our clients work while advancing the global
impact of their business solutions for a more optimistic and better world. We
are passionate about building and sustaining an inclusive and equitable
workplace where all people can develop and thrive. Enriched by our “4C’s” –
Care, Courage, Curiosity, and Collaboration – our culture supports solutions
that empower the possible.

Mid -Level
Position based out of Pune (8 -12 years)

Job Description:

Job Summary:

We are looking for a
highly experienced and motivated Senior Data Engineer with a strong background
in PySpark, ETL processes, and SQL. The ideal candidate should have deep
technical expertise in designing and building scalable data pipelines, data
integration, and transformation workflows in distributed environments. This
role will play a critical part in enabling data -driven decision -making across
the organization.

Key Responsibilities:

- Design, develop, and maintain
large -scale, distributed data processing systems using PySpark on big data
platforms (Hadoop/Spark).

- Build and automate ETL/ELT pipelines
to extract data from various structured and unstructured sources.

- Optimize and troubleshoot SQL queries
for performance, scalability, and accuracy.

- Work closely with Data Architects,
Data Scientists,



and Analysts to deliver clean, structured, and reliable
data for business use.

- Implement best practices for data
modeling, data quality, and data governance.

- Monitor and enhance data workflows to
ensure reliability and performance in production.

- Contribute to technical discussions,
architectural reviews, and code reviews.

- Mentor junior data engineers and
support their technical growth.


Required Skills &
Qualifications:

- 8–12 years of experience in Data
Engineering roles.

- Strong expertise in PySpark and Apache
Spark for large -scale data processing.

- Proven experience designing and
building ETL pipelines in production environments.

- Deep understanding and hands -on
experience in writing complex and optimized SQL queries.

- Experience working with big data
technologies (e.g., Hadoop, Hive, HDFS, Delta Lake).

- Familiarity with data warehouse
platforms like Snowflake, Redshift, or BigQuery is a plus.

- Solid understanding of data
architecture, data modeling, and data quality frameworks.

- Experience with cloud platforms (AWS,
Azure, or GCP) is preferred.

- Solid problem -solving and debugging
skills.

- Excellent communication and
collaboration skills.


Preferred
Qualifications:

- Experience with workflow
orchestration tools like Airflow, Apache NiFi, or similar.

- Knowledge of DevOps practices and
tools for data engineering (CI/CD, Git, Jenkins).

- Experience with containerization and
orchestration tools (Docker, Kubernetes) is a plus.


Education:

- Bachelor’s or Master’s degree in
Computer Science, Information Technology, Engineering, or a related field.