Software Engineer III - Data Engineer at JPMC Candidate Experience page

Mumbai, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

24 May, 26

Salary

0.0

Posted On

23 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Modeling, ETL/ELT Pipelines, Cloud Data Platforms, Oracle Databases, Big Data Technologies, Data Migration, Data Quality, Data Governance, Python, Risk Management, Regulatory Compliance, OLTP, OLAP, Snowflake, Databricks, Airflow

Industry

Financial Services

Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Data Engineer III at JPMorgan Chase within the Wholesale Credit Risk team, you will play a key role in transforming our legacy and fragmented data landscape, supporting advanced analytics and data-promoten decision-making across the organization. In this role, you will be an integral part of complex data engineering projects, modernize large-scale Oracle databases, on-premises big data platforms, and diverse data sources. You will leverage your technical expertise to design and implement robust data models and pipelines, optimize data sourcing strategies, and architect solutions for both transactional (OLTP) and analytical (OLAP) workloads. You will address challenges related to data duplication, quality, modeling, and ownership, and deliver innovative, scalable, and secure data solutions through close collaboration with data engineers, software teams, data scientists, quants, product owners, and senior stakeholders. Job Responsibilities Contribute to the design and implementation of modern, scalable data solutions across hybrid cloud and on-prem environments, supporting both OLTP and OLAP requirements. Develop and maintain high-quality data models, ETL/ELT pipelines, and data integration processes. Participate in initiatives to consolidate, de-duplicate, and migrate legacy Oracle databases and big data platforms to modern, cloud-based data platforms. Apply and promote best practices in data engineering, security, risk management, regulatory compliance, and automation. Collaborate cross-functionally with software engineering, analytics, and business teams to deliver data solutions aligned with business objectives. Ensure data quality, governance, and metadata management across all data assets. Troubleshoot and resolve complex issues related to data duplication, quality, modeling, and ownership. Present technical strategies, architecture decisions, and project updates to stakeholders. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 3+ years applied experience. Hand-on experience in data engineering, with a proven track record of leading large-scale data architecture and transformation projects in hybrid cloud and on-prem environments. Expertise in data modeling, database design, big data technologies, cloud data platforms (AWS, Azure, GCP), and modern data tools (e.g., Snowflake, Databricks, Airflow). Strong experience architecting and optimizing transactional and analytical data systems. Mastery of ETL/ELT pipelines, data migration, data quality frameworks, data governance, and metadata management. Proficiency in enterprise-grade languages (e.g., Python) and data modeling & engineering tools. Solid background in data security, risk management, and regulatory compliance. Action-oriented, decisive, drives results systematically. Skilled at assessing risk and making decisions with a holistic, big-picture perspective. Demonstrates a can-do attitude and leads by example. Detail-oriented, able to distinguish between important and urgent tasks. Preferred qualifications, capabilities, and skills Experience in banking or financial domain

Responsibilities

The role involves contributing to the design and implementation of modern, scalable data solutions across hybrid cloud and on-prem environments, focusing on developing and maintaining high-quality data models and ETL/ELT pipelines. Responsibilities also include participating in initiatives to consolidate and migrate legacy systems while promoting best practices in data engineering and security.