Data Engineer

Fortra; United States; Remoto; USD 120.000 - 180.000; Tempo pieno

Descrizione del lavoro

Fortra is seeking a Senior Data Engineer to own the design, development, and operation of reliable data pipelines and reusable datasets supporting Fortra’s cybersecurity and ML products. Embedded within the Data Science team, you will turn diverse source data into documented, versioned, and quality-controlled datasets for experimentation, evaluation, and production workflows.

Working with Data Scientists, ML Engineers, and Product Managers, you will lead data engineering design, improve pipeline

Competenze

• 7+ years in data or software engineering with production data pipelines.
• Strong Python and SQL with well-tested, documented code.
• Experience with AWS services and databases (S3, PostgreSQL, MongoDB).
• Designing reliable ETL pipelines handling large heterogeneous data.
• Familiarity with Docker, Kubernetes, Git, and CI/CD workflows.
• Understanding data security, access controls, and governance.
• Ability to collaborate with data scientists, ML engineers, and PMs.
• Experience with ML datasets, feature engineering and knowledge graphs is a plus.

Mansioni

• Lead highly complex data engineering projects with extensive latitude for independent judgment.
• Own dataset management: schemas, data dictionaries, provenance, lineage, versioning.
• Own all ETL: ingestion, retries, backfills, recovery from partial failures.
• Identify and resolve data quality issues with automated checks.
• Implement monitoring, testing, and CI/CD with ML engineers for reliability.
• Collaborate with data scientists to assemble datasets and develop ML pipelines.
• Engineer ontologies for KG applications and expand product taxonomies.
• Ensure data compliance and governance per regulatory standards.

Conoscenze

Python

SQL

Data pipelines design

Data modeling

Data governance

Cloud AWS

Security/compliance

Formazione

Advanced degree in data engineering or related field

Strumenti

Docker

Kubernetes

Jenkins

ArgoCD

MLflow

PostgreSQL

MongoDB

Git

Descrizione del lavoro

Описание:

Whether you’re an experienced professional or just getting started, your contributions matter at Fortra. If you’re passionate about tackling meaningful challenges alongside talented team members committed to helping each other succeed, all while having lots of fun, we want to hear from you. We offer competitive benefits and salaries, personal and professional development opportunities, flexibility, and much more! The Senior Data Engineer will own the design, development, and operation of reliable data pipelines and reusable datasets that support Fortra’s cybersecurity and Machine Learning (ML) products. Embedded within the Data Science team, the role will turn diverse source data into documented, versioned, and quality-controlled datasets for experimentation, evaluation, and production workflows. Working with Data Scientists, ML Engineers, and Product Managers, this engineer will lead data engineering design, improve pipeline reliability and efficiency, and establish practical standards for data quality, lineage, and governance.

Задачи:

• Lead highly complex data engineering projects with extensive latitude for independent judgment.
• Own dataset management, including schemas, data dictionaries, source provenance, data lineage, and reproducible dataset versions, ensuring datasets remain current, accurate, and fit for purpose.
• Own all aspects of the Extract, Transform, Load (ETL) process, including reliable ingestion, retries, backfills, and recovery from partial failures.
• Identify and resolve data quality issues through automated schema validation, deduplication, and missing-data checks.
• Implement monitoring, testing, and CI/CD processes in collaboration with ML engineers to ensure high data quality and system reliability.
• Collaborate closely with data scientists to:
  • Assemble high-quality datasets that meet product requirements.
  • Perform data analysis and feature engineering.
  • Develop pipelines that support ML development and evaluation.
  • Engineer ontologies for various Knowledge Graph (KG) applications.
  • Partner with product managers to define and expand taxonomies.
  • Address data compliance and governance requirements, ensuring applicable regulatory standards are met.
  • Produce reports and actionable insights using dashboards and analytical tools.
  • Support the integration of AI/ML tools into security product and service workflows.

Требования:

• At least 7 years of relevant experience in data engineering, software engineering, or related roles, including 3 years of experience building and maintaining production data pipelines.
• Relevant advanced academic experience may substitute for part of the overall experience requirement.
• Strong Python and SQL skills, including the ability to write maintainable, tested, and well-documented code.
• Experience designing reliable ETL pipelines and working with large, heterogeneous datasets, including structured and unstructured data.
• Hands-on experience with AWS, particularly S3, relational databases such as PostgreSQL, and NoSQL databases such as MongoDB.
• Experience with data modeling, schema management, dataset versioning, and automated data quality checks.
• Familiarity with Docker, Kubernetes-based environments, Git, and CI/CD workflows.
• Understanding of data security, access controls, and governance.
• Strong problem-solving and communication skills, with the ability to work independently and collaborate effectively with data scientists, ML engineers, and product managers.
• Experience supporting ML datasets, annotation workflows, and reproducible training and evaluation splits.
• Familiarity with Jenkins, ArgoCD, and MLflow.
• Experience with knowledge graphs and ontology engineering.
• Interest in cybersecurity applications.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, veteran or disability status.