[Job-32192] Senior Data Engineer - Databricks
At a glance
Senior Data Engineering role at CI&T. Remote, Brazil.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and keep Databricks pipelines running, bringing in data from APIs, databases, files and other sources
- Shape pipeline design and development, working with business and analytics teams to meet their data needs
- Protect ingested data quality, reliability, security and governance
- Use version control, data tests and CI/CD, then document engineering processes and practices
- Guide teammates and coordinate with data scientists, analysts and platform engineers
What you bring
- You have proven experience building and operating large-scale Databricks pipelines with PySpark, Delta Lake and SQL
- You bring strong Python and SQL skills plus a deep grasp of ETL/ELT, data 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 problems
- Advanced English is essential
Who this fits
This senior role suits someone ready to guide peers while building and maintaining data pipelines. It 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.