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)
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
