The Cyber Data Analytics chapter within the Enterprise Cybersecurity organization is seeking a Senior Data Engineer to join our team. You will be at the forefront of fortifying data protection product areas by building scalable data solutions, including complex data pipelines, migrations, and sophisticated data modeling. Our team serves as a proactive shield against cyber threats, supporting multiple executive leaders with high-impact analytics for decision-making.
The Expertise You Have and The Skills You BringBachelor’s or Master’s degree in computer science, Engineering, or a related technical field.
7+ years of relevant work experience in data engineering or architecture.
Strong SQL skills and knowledge of multiple RDBMS, specifically Snowflake (including SnowSQL), Postgres, SQL Server, and Oracle.
Proven experience building data pipelines using Python, with NiFi and dbt knowledge being a significant advantage.
Experience in building Power BI Reports that transform data into aesthetically appealing visuals.
Hands-on knowledge of AWS infrastructure, including S3, EC2, RDS, EKS, Batch, and CloudFormation.
Deep understanding of data modeling principles, specifically 3NF and Star Schema models.
Experience with CI/CD workflows using Jenkins and GitHub for automated deployment.
Familiarity with workload scheduling and orchestration tools like Control-M.
Proven data analysis skills to ensure data quality such as accuracy, consistency, and completeness and to identify gaps and anomalies.
Ability to work independently in an Agile environment (Scrum and Kanban) brings technical stories to completion.
Excellent communication and presentation skills
Design and build scalable data solutions, including data processing pipelines, migrations, and complex data modeling.
Identify new development opportunities within a scalable public Cloud environment to enhance organizational capability.
Collaborate with product owners and business partners to translate high-level requirements into actionable technical tasks.
Analyze and manipulate datasets to ensure rigorous data integrity, accessibility, and security throughout the entire lifecycle.
Serve as a technical mentor and thought leader, providing guidance and innovative solutions to the broader team.
Integrate automated testing and continuous validation into the sprint cycle to ensure production reliability.
Develop end-to-end solutions using distributed platform design patterns and modern analytics technologies.
Support and enhance production systems, focusing on high performance, speed, and overall system reliability.
Our Cyber Data Analytics Squad is at the forefront of enterprise cybersecurity, dedicated to providing brand new data analytics solutions. We are part of the Enterprise Cyber Security organization. Our team boasts a diverse range of skills, including data scientists, analysts, engineers, and cybersecurity experts. Together, we build a dynamic environment that fosters innovation and problem-solving, envisioning a future where our analytics solutions serve as a proactive shield against cyber threats.
Certifications:Category:Information TechnologyPlease be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.
Skills Required
- Bachelor's or Master's degree in computer science, Engineering, or a related technical field.
- 7+ years of relevant work experience in data engineering or architecture.
- Strong SQL skills and knowledge of Snowflake (including SnowSQL), Postgres, SQL Server, and Oracle.
- Proven experience building data pipelines using Python.
- Knowledge of NiFi and dbt.
- Experience building Power BI reports and visuals.
- Hands-on knowledge of AWS infrastructure (S3, EC2, RDS, EKS, Batch, CloudFormation).
- Deep understanding of data modeling principles (3NF and Star Schema).
- Experience with CI/CD workflows using Jenkins and GitHub for automated deployment.
- Familiarity with workload scheduling and orchestration tools like Control-M.
- Proven data analysis skills to ensure data quality, accuracy, consistency, and completeness.
- Ability to work independently in an Agile environment (Scrum and Kanban).
- Excellent communication and presentation skills.
- Experience integrating automated testing and continuous validation into development cycles.
- Ability to design and build scalable data solutions, including migrations and complex data modeling.
Fidelity Investments Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fidelity Investments and has not been reviewed or approved by Fidelity Investments.
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Strong & Reliable Incentives — Bonuses, commissions, and profit-sharing are presented as generous and meaningful components of total compensation, with certain roles achieving high total earnings through multiple pay streams. Variable pay is consistently framed as a positive contributor beyond base salary.
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Retirement Support — A 401(k) match up to 7% alongside additional profit-sharing up to 10% materially enhances long-term compensation. These retirement features are highlighted as standout strengths of the overall package.
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Parental & Family Support — Generous paid parental leave (16 weeks maternity, 12 weeks parental), backup dependent care, and adoption assistance provide robust family support. Hybrid work and caregiving resources further ease family responsibilities.
Fidelity Investments Insights
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