Data & AI Consultant Databricks

About Accenture: Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions — underpinned by the world's largest delivery network — Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With 492,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com

Practice Overview

Our Technology Consulting practice helps clients reimagine their technology and data landscape by designing and implementing modern, scalable and cloud-enabled solutions.

We are looking for professionals with Databricks and Data Engineering experience to support our growing Data & AI capabilities.

You will work with clients to modernize their data platforms, build scalable data pipelines and lakehouse solutions, enable enterprise analytics and AI use cases, and support their broader data transformation journey.

Key Responsibilities

As a Data & AI Consultant specialising in Databricks, you will work with multidisciplinary teams across business, data, cloud and technology to design and implement modern data solutions.

Your responsibilities may include:

Design, develop and implement scalable data solutions using the Databricks Lakehouse Platform.

Build and optimise ETL / ELT pipelines for large-scale data processing and transformation.

Develop data engineering solutions using Python, SQL, Apache Spark and/or PySpark.

Design and implement modern data lake, lakehouse and cloud data warehouse architectures.

Work with Delta Lake for reliable and scalable data storage and processing.

Support enterprise data governance, access management and data discovery using technologies such as Unity Catalog.

Integrate Databricks with cloud platforms such as Microsoft Azure, AWS or Google Cloud Platform.

Support organizations in modernising legacy data platforms and migrating data workloads to cloud-based architectures.

Design data models and transformation processes that enable analytics, reporting, machine learning and AI use cases.

Assess existing client data environments and recommend target-state architectures and transformation roadmaps.

Translate business and technical requirements into scalable data solutions.

Work with business stakeholders, architects, engineers and delivery teams throughout the solution lifecycle.

Participate in client workshops, technical discussions, solution design sessions and architecture reviews.

Identify and resolve complex data and technology challenges.

Contribute to proposals, solution development, proof-of-concepts and client presentations.

Support the development of reusable Data & AI assets, accelerators and best practices.

Where applicable, contribute to Machine Learning, Generative AI and AI-driven workloads running on Databricks.

Required Qualifications & Experience


We are looking for candidates with hands-on experience in one or more areas of modern Data Engineering and Data & AI transformation.

Core Technical Skills

Candidates should have experience with:

Databricks

Python

SQL

Apache Spark and/or PySpark

ETL / ELT and data pipeline development

Data modelling and transformation

Data Lake / Lakehouse architecture

Cloud-based data platforms

Databricks Experience

Relevant experience may include:

Development using the Databricks Lakehouse Platform

Building and managing Databricks data pipelines

Delta Lake

Unity Catalog

Databricks notebooks and workflows

Data governance and access management

Performance optimisation

Batch and/or streaming data processing

Integration of Databricks with enterprise data ecosystems

Experience with related cloud data services, data lakes, data warehouses and integration technologies is an advantage.

Education & Certifications

Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science or another relevant discipline.

Relevant Databricks certifications are an advantage.

Cloud certifications across Microsoft Azure, AWS or Google Cloud Platform are an advantage.

Certifications related to Data Engineering, Data Architecture or Data Management are also advantageous.