Senior Data Engineer (python, SQL, Informatica)
Fidelity
Senior Data Engineer
Do you thrive on solving challenges and operating in a multifaceted setting where every single day brings new experiences? Are you a Python expert passionate about solving sophisticated problems and delivering innovative, end-to-end solutions that make a real impact? If yes, the Senior Data Engineer opportunity centered around Defined Contributions (DC) could mark a positive next phase in your career development!
The Role:
The Senior Data Engineer will support the business by working on highly sophisticated Defined Contributions data consulting projects demonstrating their technical and analytical strengths within Python. We are looking for someone to join our great team of experts, who enjoy a fast-paced environment, and can provide quality work and an outstanding client and customer experience. Our group uses various service category databases, data warehouses, and other technical applications (i.e. Python, SQL, ETL, Snowflake) to identify, analyze and propose solutions to support DC consulting projects supporting our clients directly. The ideal candidate enjoys a challenge with rewarding work having direct client impact.
The Team:
The Fidelity Workplace Consulting Group is composed of over 600 professionals who advise clients on the management of their domestic benefits. We are a fast-growing business within Fidelity, providing a broad variety of services that touch on every area of benefits design, strategy, funding, communication, and delivery. While we focus on working with the Fortune 1000, we also work with Fidelity clients of all sizes. Data Consulting engages in data quality improvement efforts that span single and multiple product lines (i.e. Health and Welfare, Defined Benefit, Defined Contribution, Stock Plan Services and HR/Payroll) within the implementation and ongoing servicing client lifecycle.
The Expertise You Have and The Skills You Bring:
2+ years Defined Contributions Domain Knowledge/experience
Minimum of 3+ years in Python, including sophisticated knowledge of Python features and solid experience with data manipulation and analysis using libraries, including Pandas
Demonstrable experience in crafting and implementing ETL pipelines using Python, encompassing data extraction from various sources (APIs, databases, flat files), transformation logic, and loading into target systems.
Sophisticated SQL expertise, including writing complex queries, optimizing performance, and working with stored procedures, views, and indexing strategies.
Hands-on experience with relational databases such as SQL Server, MySQL, and/or Oracle.
Experience with Informatica or other ETL tools, including integration with Python-based workflows and data pipelines.
Strong capability to see the big picture and design end-to-end processes, from data ingestion to reporting and automation.
Excellent debugging skills
Dynamic Working
Fidelity's hybrid working model blends the best of both onsite and offsite work experiences. Working onsite is important for our business strategy and our culture. We also value the benefits that working offsite offers associates. Most hybrid roles require associates to work onsite every other week (all business days, M-F) in a Fidelity office.
At Fidelity, we are passionate about making our financial expertise broadly accessible and effective in helping people live the lives they want! We are a privately held company that places a high degree of value in creating and nurturing a work environment that attracts the best talent and reflects our commitment to our associates. We are proud of our diverse and inclusive workplace where we respect and value our associate for their unique perspectives and experiences. For information about working at Fidelity, visit FidelityCareers.com. Fidelity Investments is an equal opportunity employer. Fidelity will reasonably accommodate applicants with disabilities who need adjustments in order to complete the application or interview process. Please email us at accommodations@fmr.com if you would like to request an accommodation.