2 months ago
Pune, IndiaSenior
Responsibilities
- Design and develop scalable ETL/ELT pipelines for large-volume datasets.
- Build cloud-native data platforms, data warehouses, data marts, semantic layers, and enterprise reporting solutions.
- Implement data ingestion, transformation, data quality, reconciliation, performance optimization, lineage, governance, and retention capabilities.
- Develop Snowflake solutions using SnowSQL, Streams, Tasks, Dynamic Tables, Snowpark, Data Sharing, security, and performance-tuning practices.
- Integrate data from relational databases, APIs, event streams, and enterprise applications, including CDC and real-time processing.
- Automate deployment of data workloads and support infrastructure-as-code and workflow orchestration practices.
- Support AI-powered data discovery, data quality, metadata management, business insights, and AI-ready data platforms.
Requirements
- 5-8 years of experience in data engineering, data warehousing, and cloud data platform development.
- Strong hands-on experience with Snowflake, PySpark, Python, and SQL.
- Expertise designing scalable ETL/ELT pipelines and understanding of dimensional modeling, data warehousing, metadata-driven frameworks, distributed processing, and big data architectures.
- Hands-on experience with AWS services including S3, Glue, Lambda, EMR, Athena, Redshift, ECS/EKS, and IAM.
- Experience with Git, Jenkins, GitHub Actions, Terraform, infrastructure as code, CI/CD pipelines, and workflow orchestration tools such as Airflow.
- Experience integrating relational databases, APIs, event streams, and enterprise applications, with knowledge of CDC, Kafka, and event-driven architectures.
- Understanding of data lineage, governance, retention, regulatory compliance, Snowflake security, and cost optimization.
- Exposure to generative AI, agentic AI, LLMs, vector databases, RAG architectures, embeddings, and AI-assisted data engineering workflows.
- Preferred experience includes Oracle, Hadoop modernization, Ab Initio migration, enterprise data platform transformation, Data Mesh, Data Fabric, modern analytics architectures, and financial services or regulated industries.
- Strong analytical, problem-solving, communication, stakeholder management, and independent-working skills.
Benefits
- Full-time position.
Tech Stack
Categories
Data Engineering
About Citi
Citi is a public financial-services company offering consumer and institutional banking, credit cards, wealth management, treasury and trade solutions, and capital-markets services. It serves individuals, corporations, financial institutions, and governments in more than 160 countries and jurisdictions, earning interest and fee income from lending, payments, trading, and advisory. Founded in 1812 and headquartered in New York, it trades on the NYSE under the ticker C.