[Job-32192] Senior Data Engineer - Databricks
At a glance
Senior Data Engineering role at CI&T. Remote, Brazil.
Pay not stated Data Engineer salary
remoteroles summary, based on the employer's posting.
What you'll do
- Build and operate Databricks pipelines that combine APIs, relational databases, files and other sources
- Shape pipeline designs around data needs gathered with business and analytics teams
- Protect ingested data through quality, reliability, security and governance practices
- Use version control, data testing and CI/CD, and document engineering processes and standards
- Guide peers technically and collaborate with data scientists, analysts and platform engineers
What you bring
- You have proven experience building and managing large-scale pipelines with Databricks, PySpark, Delta Lake and SQL
- You bring strong Python and SQL skills, plus a solid grasp of ETL/ELT, warehousing and distributed processing
- You have hands-on DataOps experience with Git, CI/CD, automated tests and infrastructure-as-code
- You can work with AWS, Azure or GCP data services and troubleshoot performance, scale and reliability issues
- Advanced English is essential for this role
Who this fits
This senior role suits an experienced data engineer who can mentor peers while working with analytics, business and platform teams. The position is remote in Brazil.
From the employer
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
We are looking for a Senior Data Developer with strong knowledge in developing and maintaining data pipelines in Databricks, Medallion Architecture, integrating and transforming data from various sources, such as APIs, relational databases, files, and many others!
As a senior member of the team, you will also provide technical guidance, mentor peers, and collaborate with cross-functional teams including data scientists, analysts, and platform engineers.
As a Senior Data Developer, you will lead the design and development of robust data pipelines, integrating and transforming data from diverse data sources such as APIs, relational databases, and files. Collaborating closely with business and analytics teams, you will ensure high-quality deliverables that meet the strategic needs of our organization.
Your expertise will be pivotal in maintaining the quality, reliability, security and governance of the ingested data, therefore driving our mission of Collaboration, Innovation, & Transformation.
Key Responsibilities
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Develop and maintain data pipelines.
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Integrate data from various sources (APIs, relational databases, files, etc.).
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Collaborate with business and analytics teams to understand data requirements.
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Ensure quality, reliability, security and governance of the ingested data.
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Follow modern DataOps practices such as Code Versioning, Data Tests and CI/CD.
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Document processes and best practices in data engineering.
Required Skills and Qualifications
Must-have Skills
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Proven experience in building and managing large-scale data pipelines in Databricks (PySpark, Delta Lake, SQL).
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Strong programming skills in Python and SQL for data processing and transformation.
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Deep understanding of ETL/ELT frameworks, data warehousing, and distributed data processing.
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Hands-on experience with modern DataOps practices: version control (Git), CI/CD pipelines, automated testing, infrastructure-as-code.
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Familiarity with cloud platforms (AWS, Azure, or GCP) and related data services.
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Strong problem-solving skills with the ability to troubleshoot performance, scalability, and reliability issues.
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Proficiency in Git.
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Advanced English is essential.
Nice-to-have Skills
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Experience with data contracts, schema evolution, and ensuring compatibility across services.
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Expertise in data quality frameworks (e.g., Great Expectations, Soda, dbt tests, or custom-built solutions).
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Integration with Power BI.