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Director Data Analytics Engineer Jobs (NOW HIRING)

Job Title: Program Director, Data & Analytics Company: Prologis A day in the life As Program ... You will connect strategy to execution across Data Engineering, Analytics Engineering, and Data ...

Job Title: Program Director, Data & Analytics Company: Prologis A day in the life As Program ... You will connect strategy to execution across Data Engineering, Analytics Engineering, and Data ...

Job Title: Program Director, Data & Analytics Company: Prologis A day in the life As Program ... You will connect strategy to execution across Data Engineering, Analytics Engineering, and Data ...

The Senior Director, Data & Analytics is responsible for shaping KEEN's data vision and ... Data Engineers, and Technical Data Analysts; strengthen the broader analyst community through ...

The Senior Director, Data & Analytics will shape KEEN's data vision and transform the organization ... Data Engineers, and Technical Data Analysts; strengthen the broader analyst community through ...

Data/Analytics Engineer Job Location: Westminster CO, or Christchurch NZ Our Department: Field Systems Data/Analytics Engineer - Customer 360 Data Pipelines About the Team: The Field Systems Data ...

Collaborate closely with peers across the engineering, analytics engineering, and data science ... Direct experience in the D2C Fintech domain is preferred. * Experience managing distributed or ...

Collaborate closely with peers across the engineering, analytics engineering, and data science ... Direct experience in the D2C Fintech domain is preferred. * Experience managing distributed or ...

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Director Data Analytics Engineer information

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$73K

$194.7K

$254K

How much do director data analytics engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for director data analytics engineer in the United States is $194,709.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,500.00 and $253,000.00 per year, depending on experience, location, and employer.

What does a Director Data Analytics Engineer do?

A Director Data Analytics Engineer oversees the design, development, and implementation of data analytics solutions within an organization. They lead teams of data engineers and analysts, set the vision for data infrastructure, and ensure that data systems effectively support business goals. Their responsibilities include managing data architecture, optimizing data workflows, and collaborating with other departments to translate business needs into technical requirements. Additionally, they are often involved in strategic planning and in establishing best practices for data governance and security.

How does a Director Data Analytics Engineer typically collaborate with cross-functional teams to drive data-driven decision making?

As a Director Data Analytics Engineer, you will regularly collaborate with stakeholders across business units, such as product managers, IT, and executive leadership, to understand their data needs and translate them into actionable analytics solutions. This often involves leading a team of data engineers and analysts, facilitating regular meetings to align on project priorities, and ensuring data infrastructure supports strategic business objectives. Effective communication and the ability to present complex technical findings in a clear, business-friendly manner are essential for fostering a data-driven culture and influencing key decisions.

What are the key skills and qualifications needed to thrive as a Director Data Analytics Engineer, and why are they important?

To thrive as a Director Data Analytics Engineer, you need deep expertise in data engineering, analytics, and strategic leadership, supported by a degree in computer science or a related field and significant industry experience. Proficiency with big data platforms (such as Hadoop and Spark), cloud services (AWS, Azure, or Google Cloud), and advanced analytics tools, along with certifications in data management or analytics, is typically required. Exceptional communication, team leadership, and problem-solving skills help drive cross-functional collaboration and innovation. These skills and qualities are essential for effectively leading analytics initiatives, translating business needs into data solutions, and driving organizational growth through data-driven decision-making.

What is the difference between Director Data Analytics Engineer vs Data Analytics Manager?

AspectDirector Data Analytics EngineerData Analytics Manager
CredentialsBachelor's/Master's in Data Science, Analytics, or related field; often requires leadership experienceBachelor's/Master's in Analytics, Business, or related field; focus on team management
Work EnvironmentStrategic leadership, overseeing analytics projects, collaborating with executivesManaging analytics teams, project execution, reporting to directors or executives
Industry UsageUsed across tech, finance, healthcare, and more for high-level analytics strategyCommon in various industries for managing analytics operations

The Director Data Analytics Engineer focuses on strategic leadership and overseeing analytics engineering initiatives, while the Data Analytics Manager handles day-to-day team management and project execution. Both roles require strong technical backgrounds, but the director position emphasizes strategic planning and cross-department collaboration.

More about Director Data Analytics Engineer jobs
What cities are hiring for Director Data Analytics Engineer jobs? Cities with the most Director Data Analytics Engineer job openings:
What are the most commonly searched types of Data Analytics Engineer jobs? The most popular types of Data Analytics Engineer jobs are:
What states have the most Director Data Analytics Engineer jobs? States with the most job openings for Director Data Analytics Engineer jobs include:
Infographic showing various Director Data Analytics Engineer job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $194,709 per year, or $93.6 per hour.
Data Analytics Engineer

Data Analytics Engineer

StationMD

Maplewood, NJ โ€ข Remote

$110K - $115K/yr

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Job Title: Data Analytics Engineer

Reports to: Director, Data and Analytics

Employment: Full-Time, Exempt


Company Summary:

StationMD is a telehealth company dedicated to serving individuals with intellectual and/or developmental disabilities (I/DD). All StationMD clinicians are board-certified and specially trained to treat individuals with I/DD. Clinicians are available 24/7 via telemedicine for urgent and non-urgent medical matters. StationMD also offers scheduled psychiatry telemedicine to individuals with I/DD. In providing this suite of services, StationMD enables individuals with I/DD faster access to high-quality care and substantially reduces unnecessary medical costs.


Position Summary:

StationMD is seeking a Data Analytics Engineer to support the buildout of our enterprise data analytics platform. This role will be a core member of the Data & Analytics team and will help design, build, and operate reliable data pipelines, analytics data models, and data quality processes across key business domains.

The initial focus of this role will be supporting the execution of StationMDโ€™s data strategy, including the ingestion and transformation of core data domain into a trusted analytics platform. This role will work closely with internal data team members, business stakeholders, technology partners, and external consulting partners to build a scalable foundation for future analytics, reporting, and operational insights.

The ideal candidate is highly skilled in SQL, understands modern cloud data platform patterns, and is comfortable working across data ingestion, transformation, data quality, documentation, and production support. This position bridges analytics engineering and data platform delivery by helping convert raw source data into governed, reusable, and trusted analytics assets.



Essential Duties and Responsibilities:
  • Build and maintain ETL/ELT pipelines to ingest and transform data from healthcare, operational, contract, patient, roster, and enterprise source systems
  • Support the implementation of StationMDโ€™s enterprise analytics platform foundation, including raw, standardized, and curated data layers
  • Develop reusable ingestion and transformation patterns using Snowflake, SQL, and related data engineering tools
  • Partner with internal team members and consulting partners to implement metadata-driven pipeline controls, process logging, audit columns, and batch tracking
  • Implement data quality checks to validate completeness, accuracy, timeliness, duplicate handling, and source-to-target reconciliation
  • Help build and maintain control tables, error logging, reject handling, monitoring, and recovery processes for data pipelines
  • Support file-based ingestion patterns, including source file tracking, raw file preservation, archive/quarantine processes, and reprocessing controls
  • Develop analytics-ready data models to support operational reporting, leadership reporting, financial analysis, clinical operations, and future self-service analytics
  • Work with business stakeholders to understand data definitions, business rules, source system nuances, and reporting needs
  • Support data governance practices, including data lineage, metadata documentation, access controls, data stewardship, and metric standardization
  • Apply security and privacy best practices for sensitive healthcare data, including PHI/PII handling, data encryption, role-based access, and auditability
  • Participate in testing, validation, troubleshooting, and production support for data pipelines and analytics datasets
  • Create and maintain technical documentation, data dictionaries, runbooks, and support procedures
  • Use Git or similar version control practices to manage analytics code, promote changes across environments, and support peer review
  • Collaborate with reporting and analytics users to ensure curated datasets are reliable, understandable, and fit for business consumption
  • Experience with data modeling techniques such as star schema, dimensional modeling, slowly changing dimensions, or data vault concepts



Required Qualifications:

Education/Certification

  • Bachelorโ€™s degree in Computer Science, Statistics, Data Science, or related field
  • Advanced degree preferred.

Qualifications/Requirements

  • 3+ years of experience in data engineering, analytics engineering, business intelligence engineering, data warehousing, or ETL/ELT development
  • Strong SQL skills with experience building, testing, and optimizing data transformations
  • Experience working with Snowflake or a comparable cloud data platform such as Azure SQL, Databricks, Redshift, or PostgreSQL
  • Experience designing or supporting ETL/ELT pipelines using batch, incremental, or file-based ingestion patterns
  • Understanding of modern data platform concepts, including raw/bronze, standardized/silver, curated/gold, dimensional modeling, and analytics-ready datasets
  • Experience implementing data quality checks, reconciliation logic, audit columns, and error handling
  • Ability to troubleshoot production data issues, identify root causes, and support pipeline recovery
  • Experience documenting data pipelines, data definitions, business rules, and technical support procedures
  • Experience using Git or similar version control tools
  • Strong communication skills with the ability to work with technical teams, business stakeholders, and external partners


Preferred Qualifications:
  • Hands-on experience with Snowflake features such as stages, file formats, streams, tasks, dynamic tables, Snowpark, role-based access, and query performance optimization
  • Familiarity with PHI/PII handling, data encryption, minimal access โ€“ least privilege data access, data anonymization
  • Experience building analytics datasets for BI tools such as Qlik, Power BI, Tableau, Sigma, or similar platforms
  • Familiarity with Salesforce, Salesforce Health Cloud, Salesforce Data Cloud, or CRM-related data integrations
  • Experience with Python for data automation, validation, scripting, or pipeline support
  • Exposure to CI/CD practices for data engineering or analytics engineering
  • Experience with dbt, Airflow, Azure Data Factory, Fivetran, Matillion, Informatica, SSIS, or similar data pipeline/orchestration tools


StationMD is an equal opportunity employer.