Role: Data Engineer + AI Exposure Location : Bangalore Experience: 7 to 13 Years Notice: Immediate to 90 days a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; } Job SummaryWe 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. a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; } Key ResponsibilitiesData 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 sourcesBig 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 RedshiftAI/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 costCollaboration & Governance • Work closely with business teams, analysts, and ML engineers • Implement data governance, lineage, and compliance standards • Document workflows, pipelines, and architecturesRequired SkillsCore Data Engineering • Strong in SQL, Python • Experience with ETL tools and pipeline orchestration (Airflow, ADF, etc.) • Hands-on with data warehousing conceptsBig 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 servicesAI/ML Exposure • Experience working with data for ML models • Knowledge of ML lifecycle and data preparation • Exposure to MLOps concepts (bonus) a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; } • 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 Cognizant: Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap 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, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai 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.