Middle/Senior Data Engineer (Databricks) @ Itransition
Summary
A client-facing data engineer who designs and builds scalable data solutions and production ELT/ETL pipelines using Databricks Lakehouse, SQL, Python, and cloud platforms (Azure preferred, AWS also) across consulting engagements, while interacting with stakeholders and championing data governance.
We're looking for a Data Engineer (Databricks) who will work closely with clients across various industries to design and implement scalable data solutions tailored to their business needs. This role demands both technical expertise and soft skills, as you’ll be translating complex data requirements into actionable architectures and pipelines while engaging directly with stakeholders.
Requirements
- 3+ years of hands-on data engineering experience, ideally within a consulting or client-facing environment
- Hands-on experience with Databricks Lakehouse Platform
- Strong SQL skills and proficiency in Python
- Experience designing and deploying solutions in cloud environments (Azure preferred)
- Ability to quickly grasp diverse business domains and adapt technical solutions accordingly
- Strong communication skills to interact with both technical and non-technical client stakeholders
- Experience working in agile, fast-paced project environments with shifting priorities
- Experience with Snowflake
- Databricks or Snowflake certifications (e.g., SnowPro Core, Databricks Certified Data Engineer)
- Familiarity with BI tools such as Power BI, Tableau, or Looker
- Previous experience in sectors like finance, healthcare, retail, or manufacturing is a plus
We're looking for a Data Engineer (Databricks) who will work closely with clients across various industries to design and implement scalable data solutions tailored to their business needs. This role demands both technical expertise and soft skills, as you’ll be translating complex data requirements into actionable architectures and pipelines while engaging directly with stakeholders.
,(Interact with client stakeholders to surface data requirements, audit existing systems, and architect scalable, future-proof solutions, Design, build, and maintain production-grade ELT/ETL pipelines using modern data stack tools and frameworks, Deploy and govern cloud-based data platforms on Azure and AWS, selecting the right approach for each engagement's unique constraints, Champion data governance, security, and compliance standards, Produce clear technical documentation and lead knowledge transfer sessions that genuinely enable client teams to operate independently, Support project scoping, estimation, and reporting with delivery managers and consultants) Requirements: Databricks, SQL, Python, Azure, Communication skills, Snowflake, Power BI, Tableau, Looker Additionally: Private healthcare, International projects, English lessons, Friendly atmosphere, Integration events, No dress code, Modern office.