DataOps Team Lead - Cloud Data Platform & Pipelines

Harvey Nash Inc.; Short Hills (NJ); Hybrid; USD 140,000 - 160,000; Full time

Benefits offered by this job

Pension/401K

Paid Vacation

Medical & Dental Insurance

Job summary

Harvey Nash invites a DataOps Team Lead to shape and operate modern data pipelines across enterprise. Hybrid work in Short Hills, NJ / Hartford, CT / Charlotte, NC with 3 days onsite weekly.

You will lead data engineering, analytics, and governance, drive CI/CD for data, ensure reliability, and mentor a high‑performing team while partnering with architecture, analytics, and platform squads.

Qualifications

• 8+ years of experience in data engineering, analytics engineering, or platform engineering.
• 3+ years in a lead or senior engineering role managing data platforms or operations.
• Strong experience with cloud data platforms (Azure, AWS, or GCP).
• Experience with Databricks, or modern Lakehouse architectures.
• Excellent communication skills.
• Proven history of leading others to complete complex deliverables.

Responsibilities

• Define and evolve the DataOps operating model, including how data pipelines and platforms are designed, deployed, supported and scaled across teams.
• Lead the design and implementation of DataOps frameworks, standards, and best practices across the organization.
• Partner with Data Architecture, Analytics, AI/ML, and Platform teams to operationalize data products end‑to‑end.
• Establish operational expectations for data products/data contracts, including reliability targets, change management, and consistency of consumption for analytics and AI use cases.
• Drive adoption of automation, orchestration, and observability capabilities for data pipelines.
• Implement and manage CI/CD for data, including automated testing, deployments, and rollback strategies.
• Ensure high availability, performance, and reliability of data platforms and analytics workloads.
• Establish monitoring, alerting, and incident management for data systems, including root‑cause analysis and post‑incident improvements.
• Embed governance requirements into data operations, including data quality controls, lineage visibility, and access enforcement within pipelines.
• Monitor and optimize cloud consumption and platform costs for data workloads.
• Drive performance tuning and capacity planning for data platforms.
• Own, report and provide transparency into platform health, costs, and operational metrics.
• Lead, mentor, and grow high‑performing DataOps and data engineering team members.
• Serve as a thought leader on modern data engineering and operational practices.

Skills

Data leadership

Communication

Mentoring

Cross-team collaboration

Operational excellence

Data modeling

Regulated environments

Education

Bachelor's degree in Computer Science or MIS

Tools

Airflow

ADF

Dagster

dbt

Azure DevOps

GitHub Actions

GitLab

Job description

Job Title: DataOps Team Lead

Location: Short Hills, NJ / Hartford CT / Charlotte, NC (Hybrid working - 3 days a week)

Perm/FTE Role

US citizens and Green Card Holders and those authorized to work in the US are encouraged to apply. We are unable to sponsorH1bcandidates at this time

Job Details:

• Seeking an energetic and collaborative DataOps Team Lead responsible for establishing, scaling, and operating modern data pipelines and platforms that enable reliable, secure, and high-quality analytics across the enterprise.
• This role bridges data engineering, analytics, platform engineering, and governance to ensure data products are delivered efficiently, consistently, and at scale.
• This is a key leadership position in the next phase of the organization’s data and analytics evolution, with responsibility for shaping how data engineering work is delivered, operated, and governed across teams.
• The ideal candidate brings strong hands-on experience with cloud data platforms, CI/CD for data, operational excellence, leading teams, setting operational standards, and influencing how data engineering is practiced across the organization.

Responsibilities

• Define and evolve the DataOps operating model, including how data pipelines and platforms are designed, deployed, supported and scaled across teams.
• Lead the design and implementation of DataOps frameworks, standards, and best practices across the organization.
• Partner with Data Architecture, Analytics, AI/ML, and Platform teams to operationalize data products end-to-end.
• Establish operational expectations for data products/data contracts, including reliability targets, change management, and consistency of consumption for analytics and AI use cases.
• Drive adoption of automation, orchestration, and observability capabilities for data pipelines.
• Implement and manage CI/CD for data, including automated testing, deployments, and rollback strategies.
• Ensure high availability, performance, and reliability of data platforms and analytics workloads.
• Establish monitoring, alerting, and incident management for data systems, including root-cause analysis and post-incident improvements.
• Embed governance requirements into data operations, including data quality controls, lineage visibility, and access enforcement within pipelines.
• Monitor and optimize cloud consumption and platform costs for data workloads.
• Drive performance tuning and capacity planning for data platforms.
• Own, report and provide transparency into platform health, costs, and operational metrics.
• Lead, mentor, and grow high-performing DataOps and data engineering team members.
• Serve as a thought leader on modern data engineering and operational practices.

Qualifications Required

• Proven history of leading others to complete complex deliverables.
• Demonstrated ability to provide technical leadership through design reviews,
• architectural decisions, and operational trade-offs.
• Excellent communication skills
• 8+ years of experience in data engineering, analytics engineering, or platform engineering.
• 3+ years in a lead or senior engineering role managing data platforms or operations.
• Strong experience with cloud data platforms (Azure, AWS, or GCP).
• Experience with Databricks, or modern Lakehouse architectures.

Hands-on expertise with:

• Data pipelines and orchestration (e.g., Airflow, ADF, Dagster, dbt)
• CI/CD tools (Azure DevOps, GitHub Actions, GitLab, etc.)
• SQL and Python/PySpark
• Solid understanding of data modeling, data quality, and data lifecycle management.

Preferred

• College degree in Computer Science, Management Information systems or related
• Familiarity with streaming platforms (Event Hubs, Kafka, Kinesis).
• Experience supporting machine learning or AI workloads in production.
• Knowledge of FinOps practices for cloud cost management.
• Background in regulated or enterprise environments (financial services, insurance, healthcare).
• SAFe agile work experience or similar agile process

A reasonable, good faith estimate of the minimum and maximum base salary for this position is $140k to $160K . This position will also include a discretionary bonus or 10% that generally will be depending on a variety of factors.Employee benefitswill also be available, and details are available like Pension/401K/ Paid Vacation/ Life, Medical & Dental insurance etc.

* The pay range listed above reflects the expected starting salary /Pay rate for this role. This range may be adjusted based on market conditions, location, and other relevant factors. The Company will determine the final starting salary/Pay rate in consultation with the selected candidate(s), in full compliance with applicable laws