Senior Data Engineer (Python/ Spark/GCP)
Wells Fargo (company site, opens in a new tab)4+ yrsHyderabadOn-siteDirect career pageEst. 20–35 LPA
Posted on 31 Aug
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Wells Fargo
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Wells Fargo you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead the development and modernization of scalable data platforms on Google Cloud Platform (GCP) focused on AI/GenAI-driven data solutions.
- Design, build, and maintain optimized data pipelines and enterprise-scale ETL/ELT and streaming solutions using Python, SQL, Spark, and GCP services such as BigQuery, Dataproc, Composer, Kafka, and Pub/Sub.
- Drive cloud migration, data transformation, data quality initiatives, and implement metadata, lineage, governance, and observability practices, collaborating with cross-functional teams to deliver scalable, reliable AI-enabled data products and services.
Minimum Requirements
- Minimum 4 years of Data Engineering experience or equivalent demonstrated through work experience, training, education, or military experience.
- Strong hands-on expertise in Python, SQL, Spark, and data engineering.
- Experience with GCP services including BigQuery, Dataproc, Cloud Composer, Pub/Sub, Kafka.
- Proficiency in building large-scale ETL/ELT and streaming data pipelines with knowledge of data modeling, governance, and cloud architecture.
Ideal Candidate Profile
- Experienced in leading moderately complex data engineering initiatives within enterprise environments involving AI and GenAI data solutions.
- Skilled in integrating modern AI technologies such as large language models, vector search, semantic search, and AI-powered applications.
- Operates with a focus on engineering excellence through automation, CI/CD, monitoring, reusable frameworks, and collaborative delivery with product, platform, security, and business teams.