Role: Data Engineer + AI Exposure
Location : Bangalore
Experience: 7 to 13 Years
Notice: Immediate to 90 days
Job Summary
We are seeking a skilled Data Engineer with AI/ML exposure responsible for designing, building, and maintaining scalable data pipelines and supporting data-driven applications, including AI/ML use cases. The ideal candidate should have strong expertise in data engineering tools along with working knowledge of machine learning workflows and cloud-based data platforms.
Key Responsibilities
Data Engineering
- Design, develop, and maintain scalable ETL/ELT pipelines
- Build and optimize data architectures, data lakes, and data warehouses
- Ensure data quality, integrity, and security across systems
- Work with structured and unstructured data from various sources
Big Data & Cloud
- Develop solutions using tools such as Azure Data Factory / AWS Glue / GCP Dataflow
- Work with big data technologies like Spark, Hadoop, or Databricks
- Manage data storage solutions including S3, ADLS, BigQuery, Snowflake, or Redshift
AI/ML Exposure
- Support machine learning pipelines and data preparation for ML models
- Collaborate with Data Scientists to enable feature engineering and model deployment
- Work on AI-enabled data solutions (e.g., NLP, recommendation systems, prediction models)
- Basic understanding of ML frameworks (Scikit-learn, TensorFlow, or PyTorch is a plus)
Data Modeling & Optimization
- Design and implement data models (dimensional & normalized)
- Optimize queries and pipelines for efficiency and cost
Collaboration & Governance
- Work closely with business teams, analysts, and ML engineers
- Implement data governance, lineage, and compliance standards
- Document workflows, pipelines, and architectures
Required Skills
Core Data Engineering
- Strong in SQL, Python
- Experience with ETL tools and pipeline orchestration (Airflow, ADF, etc.)
- Hands-on with data warehousing concepts
Big Data Technologies
- Apache Spark / PySpark
- Hadoop ecosystem (optional but preferred)
Cloud Platforms (any one required)
- Azure / AWS / GCP hands-on experience
- Familiarity with cloud-native data services
AI/ML Exposure
- Experience working with data for ML models
- Knowledge of ML lifecycle and data preparation
- Exposure to MLOps concepts (bonus)
Preferred Qualifications
- Experience with Databricks / Snowflake
- Knowledge of API-based data ingestion
- Familiarity with CI/CD pipelines
- Exposure to real-time streaming (Kafka, Event Hub, etc.)
- Understanding of Generative AI or LLM integrations (added advantage)
About us
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, building the bridge between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, realize tangible returns and keep global enterprises ahead in a fast-changing world. See how at www.cognizant.com or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.
