Staff Data Engineer: Lakehouse & Cloud Data Architect

Talentify; Raritan (NJ); On-site; USD 94,000 - 152,000; Full time

Job summary

Johnson & Johnson is seeking a Staff Data Engineer to strengthen the Orthopedics Supply Chain data foundation. You will design lakehouse architectures on Databricks and AWS, building reusable data products for analytics, reporting, AI, and operational decision‑making.

You will lead architecture discussions across product, data governance, ML, and IT, delivering scalable pipelines and governance standards while mentoring engineers and coordinating vendors.

Qualifications

• Minimum four (4) years of relevant professional work experience.
• Experience in data engineering, data architecture, or platform engineering (consistent with J&J leveling).
• Strong hands‑on experience across Databricks, Apache Spark, PySpark, Spark SQL, Python, SQL, and Delta Lake.
• Strong experience with AWS cloud data services; Azure experience desirable.
• Proven expertise in modern data and lakehouse architecture, enterprise data platforms, dimensional modeling, and pipeline design.
• Experience designing batch, real‑time, and event‑based processing for enterprise‑scale workloads.
• Experience with CI/CD, Git‑based development, automated testing, deployment patterns, and production support.
• Proven skill in converting business needs into architecture, user stories, and executable delivery plans.
• Demonstrated ability to coordinate distributed engineering teams, contractors, and vendors.
• Excellent communication, facilitation, and relationship‑building skills across technical, product, and business audiences.
• Knowledge of Power BI, Tableau, or enterprise BI platforms.
• Knowledge of workflow automation tools (Power Automate, Blue Prism, UiPath, or Amazon Quick Flows).

Responsibilities

• Provide technical leadership for the Data Foundation initiative to modernize the enterprise data ecosystem through lakehouse architecture and cloud platform capabilities.
• Design complex data pipelines, integration patterns, and architecture using Databricks, AWS, Python, SQL, Spark, and Delta Lake.
• Turn business requirements and technical challenges into architecture decisions, implementation plans, and reusable patterns.
• Develop blueprints for batch, streaming, and event‑driven pipelines that support analytics, BI, AI/ML, and digital product use cases.
• Partner with Product Owners, Supply Chain teams, data governance, AI and ML groups, and IT partners to align delivery with measurable business outcomes.
• Lead architecture and design discussions, ensuring solutions meet standards for scalability, reliability, quality, security, maintainability, and cost efficiency.
• Break down large initiatives into work packages, user stories, and acceptance criteria for internal engineers and external contractors.
• Coordinate contractor and vendor execution by assigning work, reviewing deliverables, and providing technical direction.
• Set clear standards for data modeling, modularity, reuse, automated testing, CI/CD, data quality, observability, lineage, and operational support.
• Lead hands‑on development and technical reviews with Databricks, PySpark, Spark SQL, Python, SQL, dbt, and orchestration tools like Airflow.
• Champion responsible adoption of AI‑assisted engineering to improve quality, documentation, testing, and delivery velocity.
• Mentor engineers and contractors through design and code reviews and architecture guidance (no direct people‑management responsibility).
• Contribute to technical governance forums, architecture standards, and operating‑model practices that improve consistency and reuse.

Skills

Databricks

Spark

PySpark

Python

SQL

Delta Lake

AWS

CI/CD

Data Modeling

Architecture Leadership

Education

Bachelor’s degree in Computer Science / Engineering / related field

Tools

Databricks

Spark

PySpark

Spark SQL

Python

SQL

Delta Lake

AWS

Power BI

Tableau

Airflow

dbt

Terraform

Job description

Johnson & Johnson is seeking a Staff Data Engineer to strengthen the Orthopedics Supply Chain data foundation. You will design lakehouse architectures on Databricks and AWS, building reusable data products for analytics, reporting, AI, and operational decision‑making.

You will lead architecture discussions across product, data governance, ML, and IT, delivering scalable pipelines and governance standards while mentoring engineers and coordinating vendors.