Data Engineering Manager & Architect (Hybrid Leadership/Architect Role)

Arohak Inc.; Raritan (NJ); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Arohak Inc. is seeking a seasoned Data Engineering Manager/Architect to lead complex data migration and engineering initiatives in a highly regulated life sciences environment.

This hybrid leadership/architect role requires collaboration with client executives and hands-on design of enterprise data solutions on Azure and Databricks. You will serve as the primary technical and program contact for client leadership, translating requirements into scalable architectures, driving execution across

Qualifications

• 15+ years of overall Data Engineering experience with leadership/architect roles.
• Hands-on and architectural expertise in Azure and Databricks.
• Experience with large-scale data migration programs across multiple domains.
• Experience in regulated life sciences/pharma environments.

Responsibilities

• Lead data migration, data quality, and ETL initiatives on Azure and Databricks.
• Translate business requirements into scalable architectures for enterprise data platforms.
• Coordinate onshore/offshore delivery and align deliverables with Agile release cadences.
• Provide architectural leadership including data modeling, pipeline design, and schema evolution.
• Ensure compliance with governance and regulatory requirements in life sciences.

Skills

Azure

Databricks

Data Migration

Data Quality

ETL

Leadership

SAFe/Agile

Stakeholder Management

Onshore/Offshore Delivery

Regulated Environment

Tools

Azure Data Services

Databricks

Job description

Job Title: Data Engineering Manager & Architect (Hybrid Leadership/Architect Role)

Experience Required: 15+ Years

Time Zone Coverage: Eastern Time (ET) - required overlap with client leadership and onshore/offshore teams

Domain: Life Sciences (Highly Regulated Environment)

Cloud/Platform: Microsoft Azure, Databricks

About The Role

We are seeking a seasoned Data Engineering Manager/Architect to lead complex data migration and data engineering initiatives within a highly regulated life sciences environment. This is a hybrid leadership and technical architecture role - the ideal candidate is equally comfortable engaging directly with client executives and stakeholders as they are designing and overseeing the technical implementation of enterprise-scale data solutions on Azure and Databricks.

The candidate will serve as the primary technical and program-level point of contact for client leadership, translating business requirements into scalable architectures, driving execution across onshore/offshore teams, and ensuring delivery excellence in a regulated data ecosystem.

Key Responsibilities

• Work closely and daily with client leadership and business stakeholders to gather, clarify, and prioritize data migration requirements across multiple business domains/experiences.
• Architect, design, and implement end-to-end data migration, data quality, and ETL solutions on Azure and Databricks, ensuring alignment with enterprise standards and regulatory requirements.
• Own and track migration initiatives to closure - from requirements gathering through design, build, testing, and go-live.
• Partner with the Release Train Engineer (RTE) and program teams to align data engineering deliverables with broader program/Agile release cadences.
• Manage and coordinate an onshore/offshore delivery model, ensuring consistent execution, quality, and communication across distributed teams.
• Provide strong technical and architectural leadership, including guidance on data modeling, pipeline design, schema versioning/evolution, and platform best practices.
• Drive problem resolution across technical, process, and stakeholder-related issues, escalating and resolving blockers proactively.
• Take full ownership and accountability for program outcomes, timelines, and stakeholder satisfaction.
• Ensure all solutions comply with data governance, quality, and regulatory requirements specific to the life sciences domain.
• Lead stakeholder engagement activities, including status reporting, roadmap alignment, and executive communication.
• Champion best practices in data analysis, data quality frameworks, and ETL design across the engineering team.

Required Skills & Experience

• 15+ years of overall experience in Data Engineering, with proven experience in leadership/architect hybrid roles.
• Deep hands-on and architectural expertise in:
  • Microsoft Azure (cloud data services)
  • Databricks (platform architecture, pipeline design, performance optimization)
  • Data Migration - large-scale, multi-domain migration programs
  • Data Analysis and Data Quality frameworks/tooling
  • ETL design, development, and orchestration
• Demonstrated experience working in a highly regulated environment, ideally life sciences/pharma.
• Strong understanding of schema versioning and schema evolution strategies in enterprise data platforms.
• Experience partnering with an RTE (Release Train Engineer) and working within SAFe/Agile program structures.
• Proven track record managing or working within an onshore/offshore delivery model.
• Strong stakeholder management skills - able to engage confidently with client leadership and cross-functional business teams.
• Excellent problem-solving, ownership, and program-driving capabilities; comfortable being accountable for outcomes, not just deliverables.
• Ability to work core hours aligned to Eastern Time (ET).

Preferred / Nice-to-Have Skills

• Knowledge of Microsoft Dataverse and Microsoft Dynamics 365.
• Prior experience in life sciences-specific data domains (e.g., clinical, regulatory, commercial, or R&D data).
• Familiarity with data governance and compliance frameworks common in regulated industries (e.g., GxP, 21 CFR Part 11, HIPAA where applicable).

What Success Looks Like In This Role

• Client leadership views this person as a trusted technical advisor and program driver, not just an execution resource.
• Data migration programs are delivered on time, with strong quality and minimal escalations.
• Architecture decisions are scalable, well-documented, and enable clean schema evolution over time.
• Onshore/offshore teams operate cohesively under this person's technical and program guidance.
• Issues are resolved proactively, with clear ownership and communication back to stakeholders.