Principal Data Engineer

Belfast, UK

Open 7 months, first seen by us 211 days ago

Pay: Pay not listed
Work setting: Not stated
Employment: Not stated

What you’ll work on

Full posting

Lead design and build-out of cross-product data services on one governed data plane
Build batch, streaming, and event ingestion patterns with repeatable source onboarding
Own data reliability: contracts, quality checks, lineage, monitoring, and incident response
Productize customer-facing datasets, metrics, exports, and feeds with versioning and ownership
Design data models for both operational (RDS) and analytics (columnar/OLAP) stores

From the employer’s posting

Lead the design and build-out of cross-product data services for multiple product lines from one governed data plane.

Build and operationalize ingestion patterns for batch, streaming, and event data, with repeatable onboarding for new sources.

Own the operational playbook for data reliability: data contracts, quality checks, lineage, monitoring, and incident response.

Productize customer-facing data products (datasets, metrics, exports, and feeds) with versioning, documentation, and clear ownership.

Design data models that fit both operational systems (RDS) and analytics stores (columnar/OLAP), including performance and cost tuning.

Apply at Black Duck Software

Posting record

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Open 7 monthsWe first saw this posting 211 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records: Live
First seen by us: Apr 7, 2026211 days ago
Recorded sightings: 250
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 211

Up longer than most. Similar jobs usually come down between day 6 and day 54.

From 10,845 similar postings that came down. Coming down is not always a hire.

Black Duck Software is hiring

1 open job

No new data jobs since May

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
AWS
GCP

Where the posting names them

- Significant experience building and operating production data platforms at scale, including on-call and operational ownership. - Strong SQL skills and strong Python skills, used to build pipelines, services, and automation. - Hands-on experience running cloud systems on AWS and Google Cloud (IaaS level: compute, storage, networking, IAM).

- Strong SQL skills and strong Python skills, used to build pipelines, services, and automation. - Hands-on experience running cloud systems on AWS and Google Cloud (IaaS level: compute, storage, networking, IAM). - Practical experience with both operational databases (RDS-style) and analytics stores (columnar/OLAP), including performance tuning.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Black Duck Software, Inc. helps organizations build secure, high-quality software, minimizing risks while maximizing speed and productivity. Black Duck, a recognized pioneer in application security, provides SAST, SCA, and DAST solutions that enable teams to quickly find and fix vulnerabilities and defects in proprietary code, open source components, and application behavior. With a combination of industry-leading tools, services, and expertise, only Black Duck helps organizations maximize security and quality in DevSecOps and throughout the software development life cycle.

What you’ll do

Lead the design and build-out of cross-product data services for multiple product lines from one governed data plane.
Define the “customer data plane” model: canonical customer identifiers, shared dimensions, and consistent facts used across products.
Build and operationalize ingestion patterns for batch, streaming, and event data, with repeatable onboarding for new sources.
Own the operational playbook for data reliability: data contracts, quality checks, lineage, monitoring, and incident response.
Implement and run access methods that make data usable: curated datasets, secure query interfaces, and product-ready data APIs where needed.
Productize customer-facing data products (datasets, metrics, exports, and feeds) with versioning, documentation, and clear ownership.
Design data models that fit both operational systems (RDS) and analytics stores (columnar/OLAP), including performance and cost tuning.
Ensure data products also power ML workflows: trusted training datasets, feature-ready outputs, and consistent definitions for decision-making.
Enable AI automation by delivering reliable, low-latency, governed data products that can be used safely in automated workflows.
Partner closely with product, engineering, and security stakeholders to align data products to roadmap priorities and customer outcomes.
Raise the technical bar through architecture reviews, standards, and mentoring—while staying hands-on in key systems.

Required

Significant experience building and operating production data platforms at scale, including on-call and operational ownership.
Strong SQL skills and strong Python skills, used to build pipelines, services, and automation.
Hands-on experience running cloud systems on AWS and Google Cloud (IaaS level: compute, storage, networking, IAM).
Practical experience with both operational databases (RDS-style) and analytics stores (columnar/OLAP), including performance tuning.
Strong data modeling ability, including schema evolution, conformed dimensions, and “one source of truth” metric definitions.
Track record of delivering data products that other teams or customers depend on, with clear contracts and reliability expectations.
Ability to make sound engineering tradeoffs across latency, accuracy, cost, and security without creating brittle complexity.
Experience with lakehouse patterns and open table formats (or similar), including governance and table maintenance.
Experience with orchestration and streaming systems used in production (batch + real-time), and managing backfills safely.
Familiarity with ML data needs (training/serving splits, feature-ready datasets, evaluation datasets) and AI-adjacent workflows.

Preferred

Experience building self-service data platforms (catalog, discoverability, access controls) used by multiple teams.
Experience in regulated or security-sensitive environments, including retention, auditing, and data access controls.

Work model, location & travel

Location: Belfast, UK
Reports to: VP of Data Engineering
Work model: Hybrid (details TBD)
Collaboration hours: Flexible; overlap with UK and US time zones
Travel: Minimal

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Black Duck is an equal opportunity employer. We consider all applicants for employment without regard to race, color, national origin, religion, sex, gender identity or expression, age, disability, sexual orientation, veteran or military service status, or any other characteristic protected by applicable law. Black Duck complies with all applicable laws prohibiting employment discrimination in every jurisdiction where it operates and provides reasonable accommodations to individuals with disabilities in accordance with applicable law.

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