Lead the Industrial Group data governance program, KPI framework, and business intelligence capabilities to enable data-driven decision making across the organization.
Locations (3)
Buffalo, New York, United States
United Kingdom, United Kingdom
Europe, Europe
Compensation
The base pay range for this opportunity is $USD130,000 - $USD180,000 per year, or equivalent benchmark in Europe/UK.
Responsibilities
Lead the Industrial Group data governance program, including governance processes, operating models, standards, policies, and stewardship activities.
Partner with Corporate Data Management to align Industrial Group practices with enterprise data standards and governance frameworks.
Establish accountability for critical business data through defined data ownership and stewardship structures.
Cloud Data Engineer working within the AI & Engineering team to transform technology platforms, design and develop scalable cloud-based data solutions, and manage AI/ML platforms.
Compensation
A reasonable estimate of the current range is $116,200 to $229,100.
Responsibilities
Transform technology platforms and drive innovation
Re-imagine and re-engineer operations and processes critical to business
Build, deploy, and operate cutting-edge engineering capabilities
Design and develop scalable cloud-based data solutions
Lead small engagements and cross-functional teams
Requirements
Bachelor’s degree in computer science, engineering, data science, artificial intelligence, or information technology
Provides technical direction, guidance and support for architectural development that encompasses multiple technology disciplines, platforms and applications.
Compensation
Pay Range: $111,605.00 - $131,300.00
Responsibilities
Design and implement scalable Databricks Lakehouse architectures supporting enterprise data processing, analytics, and high-volume workloads.
Develop data solutions using Databricks, Python, PySpark, Databricks SQL, and Delta Lake.
Modernize and migrate complex Oracle SQL and PL/SQL workloads to Databricks and cloud-based data platforms.
Design and implement high-volume ETL/ELT pipelines, data ingestion, transformation, orchestration, and integration solutions.
Optimize Databricks performance, including SQL queries, data layouts, compute utilization, jobs, and distributed data processing.
Build, extend, and maintain a shared data platform on Databricks Lakehouse for multiple group companies.
Compensation
Salary range $90,000 to $125,000. Ultimate salary offered will be based on factors such as applicant experience and geographic location. Our company offers a competitive benefits package and bonus eligibility on top of base.
Responsibilities
Build and configure new Databricks workspaces, Unity Catalog structures, and compute resources across environments
Design and develop new Databricks Terraform modules for repeatable provisioning
Manage and optimize compute configurations balancing cost, performance, and isolation
Implement and maintain platform-level security controls
Build and maintain Azure DevOps pipelines for automated deployment
Requirements
Nice to have: Experience with TMNAS engineering standards
Nice to have: Experience with Azure DevOps CI/CD pipelines or equivalent
Nice to have: Experience with Bicep / ARM templates
Nice to have: Experience supporting multi-tenant or multi-environment platform configurations
Lead design and delivery of scalable technical solutions for client engagements in cloud data engineering.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $134500 to $265100.
Responsibilities
Lead small engagements or key workstreams within larger technology transformation programs for clients
Manage cross-functional distributed delivery teams and client relationships across the engagement lifecycle, while contributing to proposal and business development efforts
Oversee quality of team deliverables and recommendations while contributing to hands‑on solution delivery across distributed teams
Requirements
Bachelor’s or master’s degree in computer science, engineering, data science, artificial intelligence, information technology, or a related field
Nice to have: Master’s degree
Nice to have: Experience with Delta Lake, Unity Catalog, or MLflow
Nice to have: Experience with Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
Nice to have: Experience designing batch and streaming data pipelines
Develop and optimize data pipelines using Python, PySpark, and SQL within the Databricks Lakehouse platform and apply Medallion architecture patterns to organize, transform, and manage data across data layers.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $107,700 to $179,500.
Responsibilities
Develop and optimize data pipelines using Python, PySpark, and SQL within the Databricks Lakehouse platform
Apply Medallion architecture patterns to organize, transform, and manage data across data layers
Perform performance tuning for Databricks workloads and SQL queries
Configure row-level and column-level security and manage data lineage and sharing in Unity Catalog
Implement continuous integration/continuous delivery (CI/CD) and testing processes for Databricks workflows
Requirements
Bachelor’s degree
Nice to have: Experience using Medallion architecture in the Databricks Lakehouse platform
Nice to have: Experience configuring row-level and column-level security, data lineage, and data sharing in Unity Catalog
Nice to have: Experience implementing continuous integration/continuous delivery (CI/CD) and testing processes for Databricks
Facilitate governance councils and working groups to resolve data definition, ownership, quality, and prioritization matters.
Develop and maintain business glossaries, data dictionaries, metadata standards, critical data element definitions, and supporting documentation.
Requirements
Bachelor's degree in Business, Information Systems, Data Analytics, Engineering, Finance, or a related field, or a combination of education and equivalent experience.
Nice to have: Experience in manufacturing, aerospace, industrial, or another complex regulated environment
Nice to have: ERP transformation or modernization initiatives
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