Databricks Engineer

Position Description
This is a rare opportunity to step into a Senior Consultant role on a modern data platform with a clear supported path to becoming a Databricks Architect. Youll be hands on with Databricks and the Lakehouse ecosystem from day one while being deliberately mentored into architecture: design reviews solution patterns stakeholder conversations and technical decision making.
This role is located in Houston TX and can be performed in a Hybrid model.

What makes this role stand out:

. Defined growth path: Structured mentorship from experienced architects with increasing ownership of design decisions over time. We invest in your development rather than expecting you to arrive fully formed.
. Modern technology stack: Work with current Databricks capabilities (Delta Lake Unity Catalog Delta Live Tables Workflows MLflow) across major cloud platforms.
. Variety and visibility: Consulting exposure across industries and problem types so your skills broaden quickly and you build a strong professional profile.
. Collaborative team culture: Work alongside engineers architects analysts and data scientists who share knowledge openly run design reviews and value curiosity.
. Learning support: Access to certifications (Databricks and cloud) training time and conference or community opportunities.

Future Duties and Responsibilities

. Design build and optimize scalable data pipelines (batch and streaming) on Databricks using PySpark Spark SQL and Delta Lake.
. Implement medallion architecture patterns (bronze/silver/gold) and apply data modeling best practices.
. Develop and maintain orchestration using Databricks Workflows and/or tools such as Azure Data Factory or Airflow.
. Apply data governance security and access control practices (e.g. Unity Catalog role based access lineage data quality).
. Tune performance and manage cost across clusters jobs and storage.
. Build CI/CD and DevOps practices for data workloads (Git automated testing infrastructure as code deployment pipelines).
. Participate in solution design sessions and architecture reviews progressively leading design for components and then full solutions.
. Translate business requirements into technical designs and communicate trade offs clearly to technical and non technical stakeholders.
. Produce clear technical documentation including design documents and architecture diagrams.
. Mentor junior engineers through code reviews and knowledge sharing.
. Contribute to reusable frameworks accelerators and best practice standards for the wider practice.
. Work with the team on a personal development plan toward an architect role taking on stretch assignments such as pre sales support technical assessments and platform roadmaps.

Required qualifications to be successful in this role
Essential (must have):

. 4 years of experience in data engineering with at least 2 3 years of hands on Databricks experience.
. Strong proficiency in Python (PySpark) and SQL.
. Solid understanding of Apache Spark internals and performance tuning.
. Hands on experience with Delta Lake and lakehouse design patterns.
. Experience working on at least one major cloud platform (Azure AWS or GCP).
. Experience building production grade ETL/ELT pipelines including batch and streaming.
. Working knowledge of data modeling (dimensional lakehouse) and data warehousing concepts.
. Experience with Git and CI/CD practices.
. Strong communication skills and the ability to work directly with clients and stakeholders.
. Demonstrated interest in and aptitude for growing into an architecture role (curiosity about design trade offs why behind decisions and big picture thinking). Desired (nice to have):
. Databricks certifications (e.g. Data Engineer Associate/Professional Solutions Architect).
. Cloud certifications (e.g. Azure Data Engineer AWS Data Analytics Google Professional Data Engineer).
. Experience with Unity Catalog Delta Live Tables and Databricks Asset Bundles.
. Infrastructure as code experience (Terraform Bicep or similar).
. Exposure to data governance security and compliance frameworks.
. Experience with ML/MLOps workflows (MLflow feature stores).
. Prior consulting or client facing delivery experience.
. Experience leading or mentoring junior team members.
. Familiarity with data migration or modernization projects (e.g. legacy warehouse to lakehouse).
#DICE
#LI-SG2



Other Information:
CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set level experience relevant training and licensure and certifications. To support the ability to reward for merit based performance CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $98100.00 $159800.00.
CGIs benefits are offered to eligible professionals on their first day of employment to include:
. Competitive compensation
. Comprehensive insurance options
. Matching contributions through the 401(k) plan and the share purchase plan
. Paid time off for vacation holidays and sick time
. Paid parental leave
.Learning opportunities and tuition assistance
. Wellness and Well being programs

• Azure
• Cloud Data Platform Design
• Databricks
• Python

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