Data Engineer (Cyber)

Fidelity TalentSource is your destination for discovering your next temporary role at Fidelity Investments. We are currently sourcing for a Data Engineer to work in the Cyber Security Business unit in Merrimack, New Hampshire.

The Fidelity Cybersecurity Engineering team is seeking a highly skilled Data Engineer to join our core datastore project, contributing to the design and build phases as the datastore is developed, which will drive access visibility, risk analysis, and automation across our Identity & Access Management (IAM) and IGA functions.

This engineer will be a key contributor to our data-driven IAM vision, enabling secure decision-making and operational intelligence, which involves the design, data engineering, analysis, data modelling, ETL, and ingestion of data along with the opportunity to analyse and draw key insights from collected data.

The ideal candidate will have strong experience with SQL Managed Instances in Azure cloud, as well as a solid understanding of modern data engineering best practices and experience in Agile software delivery. Core Azure SQL or MSSQL server hand-on development experience within last 3 years is a requirement.

You will be responsible for designing, developing, and maintaining robust data pipelines and solutions for the provision of data and insights to critical applications across multiple areas of the organization. Additionally, you will help define, implement, and advance data engineering practices, standards, and strategies, contributing to the progression of modern engineering practice across our platforms and teams.

Key Responsibilities:

Design, develop, and maintain high-quality data pipelines and solutions for core applications.

Perform comprehensive data analysis and modelling to support business requirements.

Develop and maintain ETL processes for efficient data ingestion and transformation, experience with SnapLogic would be a plus.

Ensure the performance, security, and scalability of data solutions.

Collaborate with analysts and stakeholders to define, design, and implement data solutions.

Participate in code and design reviews to maintain high data engineering standards.

Contribute to the continuous improvement of data engineering practices, standards, and strategies.

Implement and maintain CI/CD pipelines to ensure smooth and efficient data ingestions and delivery.

Work closely with product owners, technical leads, and architects to influence technical improvements.

Required Expertise:

Passion for data engineering and a commitment to excellence.

Degree in Computer Science, Data Engineering, Information Technology, or equivalent.

Minimum of 5 years of enterprise data engineering experience and advanced knowledge of data architecture and database technologies.

Strong experience with MS SQL, understanding of SQL MI in Azure cloud a plus.

Proficiency in data analysis, data modelling, and ETL processes.

Familiarity with data warehousing concepts and technologies.

Experience working in a CI/CD environment with tools like Git SCM, Jenkins, and Docker.

Familiarity with Agile practices and experience delivering data solutions in an Agile environment.

Skills and Attributes:

Excellent analytical, problem-solving, communication, and organizational skills.

Ability to prioritize and manage multiple data-related tasks simultaneously.

Strong team player with a collaborative and positive attitude.

Ability to work independently under general direction.

Commitment to quality and adherence to data engineering best practices.

Value You Deliver:

Deliver high-quality, timely, cost-effective, and maintainable data solutions in an Agile environment.

Contribute to test automation code and practices for data pipelines.

Participate in data engineering practices such as code and design reviews, and define source control, environment, and build and deployment strategies.

Collaborate with product owners, technical leads, and architects to drive technical improvements.

Share innovative data engineering practices and knowledge with team members.

Drive data reconciliation and health validation checks.

Team Culture:

Passionate about solving complex data problems.

Enjoy working in teams, collaborating, sharing, and learning.

Self-motivated, take initiative, and make decisions with a bias for action.

Committed to quality, strong data engineering standards, and building with testability, scalability, and resiliency in mind.

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 all business days of every other week in a Fidelity office.