Sr Databricks Data Engineer
PowerToFly
- Phoenix, Arizona, United States
- Phoenix, Arizona, United States
Über
Recruiting for this role ends on 07/03/2026.
Responsibilities
Champion Best Practices: Establish, document, and promote best-in-class approaches for data architecture, integration, and modelling.
Pipeline Ownership: Oversee the design, development, and maintenance of robust data pipelines and data architectures that support large-scale, enterprise data needs.
Drive Excellence: Initiate and manage efforts to improve data quality, operational efficiency, and process scalability.
Team and Technology Lead: Evaluate, pilot, and integrate new big data and analytics technologies, ensuring the organization remains at the cutting edge. Lead, coach, and develop teams of data engineers and architects, fostering technical growth and effective project delivery.
Data Governance: Consult on, design, and implement governance, security, and compliance strategies tailored to modern cloud data ecosystems.
Communication: Communicate technical concepts and business value to diverse stakeholders, including executives, business leads, and technology teams.
DevOps and Automation: Oversee the implementation of CI/CD practices with tools such as Azure DevOps, AWS Code Pipeline, Jenkins, TFS, or PowerShell for streamlined deployments and operations.
Provide clear guidance to others.
Required Qualifications
Five or more years of hands‑on experience in data engineering with a focus on Databricks on AWS, Azure, or GCP.
Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud‑native databases, storage solutions, and distributed compute platforms.
Experience with data warehousing, third normal form (3NF), dimensional modelling, enterprise data lakes, incremental data loads, and metadata‑driven ingestion and data quality frameworks using PySpark.
At least one year of leading complex, cross‑functional data projects and technical teams, including experience with Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and performance optimisation of data engineering pipelines, code, and compute resources.
A bachelor's degree in Computer Science, Engineering, or a related field.
Ability to travel up to 50% on average.
Limited immigration sponsorship may be available.
Preferred Qualifications
Master's degree in Computer Science, Engineering, or a related field.
Experience in one or more of AWS, Azure, and GCP cloud ecosystems and associated big data services.
Experience tuning and optimizing performance in Databricks and Apache Spark environments.
Experience with Databricks Lakeflow.
Experience with artificial intelligence and machine learning solutions.
Additional Skills & Attributes
Ability to work independently and collaborate as part of a team.
Effective written and verbal communication skills.
Meticulous attention to detail and quality of work product.
Ability to build and sustain professional relationships.
Ability to lead projects or workstreams.
Ability to manage and prioritise multiple tasks in a fast‑paced and dynamic environment.
Strong interpersonal skills and professional demeanor.
Ability to meet deadlines.
Team Deloitte's Core AI & Data practice helps organisations modernise data platforms, strengthen enterprise data foundations, and scale analytics and artificial intelligence across the business. The team works with clients to architect, engineer, and deploy cloud‑based data solutions that improve decision‑making, enable innovation, and support large‑scale transformation. Practitioners collaborate across business and technology functions to solve complex challenges in data modernisation, governance, platform engineering, and insight delivery.
Compensation The wage range for this role is $137,500 to $193,600. You may also be eligible to participate in a discretionary annual incentive programme.
Deloitte is an equal‑opportunity employer and welcomes diversity.
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Sprachkenntnisse
- English
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