Sr Data Engineer

Job Description Summary

Responsible for leading the requirements, design, development, and implementation of data engineering and analytics solutions to support cybersecurity initiatives. Will be supporting data analysts, solution architects, data engineers and product managers to deliver data analytical and reporting solutions. This role involves working with large-scale data systems, ensuring data integrity, and leveraging analytics to identify and mitigate cyber threats. The individual will collaborate with cross‑functional teams, including cybersecurity, IT, and business units, to deliver high‑quality solutions that align with organizational goals.

In this role, you will:

• Handle multiple projects across multiple data domains.
• Execute the Data strategy aligned with organizational goals.
• Gather requirements, Design and implement scalable data pipelines to process and analyze large volumes of cybersecurity data.
• Develop and maintain data models, schemas, and architectures to support analytics and reporting.
• Ensure data quality, integrity, and security throughout the data lifecycle.
• Collaborate with Data analytics and visualization team for designing dashboards, reports, and visualizations to communicate insights to stakeholders.
• Develop and maintain an integrated data architecture spanning the relational and non‑relational data landscape.
• Manage Extract, Transform & Load (ETL) framework and maintain the quality and timeliness of the data ingestion and transformation jobs.
• Drive reusability and ensure extensibility of overall data architecture.
• Manage technical data dictionaries and support businessaries.
• Lead data profiling and data analysis for source systems, manually maintained data, machine or sensor generated data and target data repositories.
• Standardize automated Extract, Transform & Load (ETL) jobs based on data mapping specifications.
• Streamline data feeds to downstream systems/products and recommend alternatives to minimize the impact.
• Lead the efforts to build Data Quality (DQ) rules.

• Bachelor’s degree from accredited university or college with a minimum of 5 years of professional experience, OR Associate’s degree with a minimum of 8 years of professional experience, OR High School Diploma with a minimum of 10 years of professional experience.
• Minimum 5 years of professional experience in data engineering.
• Note:
  
  Military experience is equivalent to professional experience.

• Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job.

• Extensive experience in data engineering, analytics, and cybersecurity domains.
• Proficiency in programming languages such as Python or Java.
• Expertise in cloud platforms (e.g., AWS, Azure).
• Strong expertise in AWS concepts like Serverless Architecture, AWS Data cataloging – Glue, AWS Crawlers, Amazon S3, Automated ETL solutions.
• Hands‑on experience in programming languages like Java, Python, Power Shell.
• Hands‑on experience in writing SQL scripts for Oracle, MySQL, Postgre
  
  SQL.
• Exposure to unstructured datasets and ability to handle XML, JSON file formats.
• Conduct exploratory, descriptive, predictive data analysis and generate visual summaries of data. Identify data quality issues proactively.

• Experience with machine learning frameworks, LLMs (AWS Bedrock, AWS Sage Maker).
• Familiarity with cybersecurity tools like SIEM, IDS/IPS, and threat intelligence platforms.
• Certifications such as CISSP, CISM, or AWS Certified Data Analytics.
• Exposure to cyber data domains.

• Stay updated on emerging technologies and trends in data engineering and cybersecurity analytics.
• Provide technical guidance and mentorship to junior team members.
• Lead the evaluation and implementation of new tools and technologies to enhance capabilities.

• Demonstrates ability to lead and work in a matrix organization structure.
• Highly self‑motivated, able to work independently and accommodate multiple time zones.

The…