Data Engineer

About Persistent We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what's next.

Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above.

We work with many industry-leading organizations across the world, including 12 of the 30 most innovative global companies, 60% of the largest banks in the US and India, and numerous innovators across the healthcare ecosystem.

Our disruptor's mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum by reporting $1,

• M revenue in FY25, delivering 18.8% Y-o-Y growth.

Our 23,900+ global team members, located in 19 countries, have been instrumental in helping the market leaders transform their industries.

We are also pleased to share that Persistent won in four categories at the prestigious

We were included in the Dow Jones Sustainability World Index, setting high standards in sustainability and corporate responsibility.

We were awarded for our state-of-the-art learning and development initiatives at the 16th TISS LeapVault CLO Awards.

In addition, we were cited as the fastest-growing IT services brand in the

Throughout our market-leading growth, we've maintained a strong employee satisfaction score of

About Position : Please mention a brief description of the position.

Role : Data Engineering lead Location : Sao Paulo Brazil – (Hybrid - 2-3 days a week in office) Experience : 10+ Years Job Type : Full Time Employment.

Job Summary : We are seeking a highly skilled and hands-on Senior Data Engineer with strong expertise in Python, PySpark, ETL pipelines, and cloud-based data platforms.

The ideal candidate will have a proven track record of designing and implementing scalable data solutions, with deep technical proficiency in data ingestion, transformation, and migration processes.

Key Responsibilities : Design, develop, and maintain scalable ETL / ELT pipelines using Python and PySpark.

Work with large-scale data ingestion and migration projects across cloud and on-premise environments.

Collaborate with cross-functional teams to understand data requirements and deliver robust data solutions.

Optimize data workflows for performance, reliability, and scalability.

Implement and manage data lake and data warehouse architectures.

Ensure data quality, integrity, and governance across all stages of the pipeline.

Utilize AWS services (especially S3, Glue, Lambda, etc.) for cloud-native data engineering solutions.

Participate in code reviews, technical design discussions, and mentoring junior engineers.

Required Skills & Qualifications : Strong hands-on experience in Python and PySpark for data processing and transformation.

Proven expertise in building and managing ETL pipelines in production environments.

Solid understanding of data warehousing concepts and experience with platforms like Snowflake, Redshift, or BigQuery.

Experience with cloud platforms, preferably AWS (S3, Glue, EC2, Lambda).

Ability to solve complex technical scenarios related to data ingestion, transformation, and migration.

Familiarity with CI / CD pipelines and version control tools like Git.

Excellent problem-solving and communication skills.

Preferred Skills : Experience with Apache Airflow or other workflow orchestration tools.

Knowledge of DevOps practices in data engineering.

Exposure to C#, .

NET, ReactJS is a plus but not mandatory.

Understanding of data governance, security, and compliance in cloud environments.

Educational Qualifications : Bachelor's or Master's degree in Computer Science, Information Technology, or related field.

Let's unleash your full potential at Persistent For more detail, please contact –