HYDERABAD · FULLTIME
Senior Software Engineer
Wells Fargo
Hyderabad · onsite · Posted 57d ago
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Undisclosed4–9 yrsfulltimeHyderabad
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Section · 01
About this role
Job Summary
About this role: Wells Fargo is seeking a Senior Software Engineer.
This is for Data Engineering to join the CALM (Corporate Asset and Liability Management) Data Engineering team within the Enterprise Functions Technology (EFT) organization. In this role, you will be responsible for designing, developing, optimizing, and maintaining metadatadriven, scalable, highperformance data engineering frameworks that power critical financial risk processes across Corporate Treasury.
You will work independently to build resilient data pipelines, APIs, wrappers, and supporting components to enable reliable data ingestion, transformation, validation, and delivery across cloud and onprem ecosystems. This position plays a key role in Data Center exit migrations, DPC onboarding, and enterprise-wide modernization initiatives.
The role requires deep technical expertise, handson problemsolving, and technical leadership in distributed data engineering, cloud platforms, data quality, and performance engineering.
Responsibilities - Lead moderately complex initiatives and deliverables within technical domain environments
- Contribute to large scale planning of strategies
- Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments
- Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures
- Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements
- Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals
- Lead projects and act as an escalation point, provide guidance and direction to less experienced staff
- 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Strong years of Software Engineering experience OR equivalent (industry, training, military, education).
- Hands-on experience with Python,SQL, andbashscripting for automation.
- Strong experience building big data pipelinesusing Apache Spark, Hive, Hadoop.
- Experience with Autosys/Airflow or similar orchestration tools.
- Working knowledge of REST APIs,Object Storage,Dremio, and CI/CD pipelines.
- Strong troubleshooting and problemsolving capabilities.
- Solid foundation in data modeling(conceptual/logical/physical) and database design.
- Platform DevOps
- Cloud-native engineering experience serverless, managed Spark, event-driven architectures.
- Familiarity with containerization (Docker, K8s) and workflow operators.
- Strong experience implementing test automation for data pipelines (unit, contract, integration tests).
- Data Lakehouse Storage
- Handson with optimization techniques: clustering, Zordering, vectorized IO (Parquet/ORC), compaction.
- Experience implementing Medallion architectures and governed ingestion zones.
- Advanced Data Engineering
- Experience architecting pipelines using distributed systems patterns (shuffle optimization, spill, broadcast, storage layouts).
- Experience with streaming frameworks like Spark Structured StreamingorApache Flink.
- Data Quality Governance
- Knowledge of data governance platforms (Collibra, Alation, Purview).
- Understanding of financial data controls, validation rules, reconciliation checks, and compliance (SOX/PCI).
- Experience implementing lineage, observability, drift detection.
- GenAI for Data Engineering
- Applying GenAI for metadata extraction, data anomaly detection, automated documentation, or pipeline optimization.
- Domain Expertise
- Exposure to financial risk, treasury functions, or Asset Liability Management (ALM) processes.
- Deliver high-quality engineering outcomes during Data Center exit migrations and DPC onboarding, ensuring validations, automation, and production readiness.
- Collaborate with cross-functional teams to build scalable, highperformance data solutions using Python, SQL, Spark, Iceberg, Dremio, and Autosys.
- Design, build, test, deploy, and maintain large-scale structured and unstructured data pipelines using Python, SQL, Apache Spark, and modern data lake/lakehouse technologies.
- Develop and optimize metadata-driven pipelines, wrappers, ingestion frameworks, and validation layers to support CALM data workflows.
- Build and maintain high-quality ELT/ETL pipelines following best practices in reliability, performance, observability, and reusability.
- Engineer and optimize Spark pipelines for large-scale batch and streaming workloads (partitioning, caching, Catalyst optimization, AQE, Tungsten).
- Work with open table formats such as Iceberg, Delta, or Hudi for versioned data, time-travel, compaction, and schema evolution.
- Implement Medallion (Bronze/Silver/Gold) architecture patterns for modern lakehouse systems.
- Implement automated data quality frameworks using tools such as Great Expectations/Deequ or custom validators.
- Build data health monitoring frameworks with SLAs/SLOs, anomaly detection, and lineage capture.
- Ensure strong validation layers during Data Center exits, migration programs, and DPC onboarding.
- Build RESTful and metadata APIs using Python frameworks (FastAPI/Flask) to enable secure, governed data access.
- Collaborate with application teams to integrate data access patterns and platform services.
- Design and deploy data pipelines in cloud platforms (AWS, Azure, GCP) leveraging managed compute, orchestration, and storage.
- Build CI/CD workflows and infrastructure automation using Jenkins, GitHub Actions, Azure DevOps, Terraform, or Helm.
- Apply secure engineering principles including IAM, secrets management, encryption standards, and network controls.
- Build resilient orchestration flows using Autosys or equivalent tools.
- Apply modular design with retries, alerts, SLAs, and workflow dependency management.
- Work with cross-functional Agile teams (Product, Architecture, QA, Treasury SMEs).
- Analyze technical requirements, evaluate design alternatives, and provide recommendations aligned with enterprise standards.
- Independently deliver complex engineering tasks and contribute to architecture/roadmap discussions.
Sourced from naukri
Section · 02
Skills
AlmAutomationBashAzure DevopsAgileApache SparkCI/CD Pipelinescloud platformsapisApacheautosysCatalystclusteringcachingamazon web servicesapache flinkapache airflowAnomaly DetectionAlationcloudArchitectureMicrosoft AzureBig Data
Section · Company
About Wells Fargo
Wells Fargo
Financial Services
20k+
employees
1852
174 years old
Bengaluru/Bangalore, Karnataka
India
About
Wells Fargo works to create positive social impact in the communities it serves by supporting housing affordability, small business growth, financial health, and a low-carbon economy.
Industries
Financial Services
Employee ratings
8,681 reviews
3.6/ 5
Culture
3.5
Career growth
2.9
Work-life
3.8
Employees rate it well for
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