CI&T05.03.26
AI SCORE 8.5

Mid-Senior Data Developer - Remote Position in Brazil

$90K–$120K/year

About the Role

We are seeking a Mid-Senior Data Developer to join our team remotely. In this role, you will be a key player in transforming our data architecture by migrating our on-premise Data Warehouses to a modern cloud-based Data Lakehouse architecture using Microsoft Azure. You will work closely with a team of experts to implement scalable and efficient data solutions that leverage the power of AI and advanced data engineering practices.

What You'll Do

  • Design and implement complex, scalable data architectures using Python/PySpark and SQL, ensuring high availability and low operational costs.
  • Define modeling standards (Medallion Architecture) for the Lakehouse, ensuring that structures like Star Schema and One Big Tables (OBTs) meet both technical performance and business needs.
  • Establish and promote CI/CD practices, automated data quality testing, and proactive monitoring of costs and performance in the Databricks/Azure environment.
  • Act as the focal point for resolving complex issues, mentoring less experienced professionals, and positively influencing the engineering culture of the team.
  • Collaborate with stakeholders to translate ambiguous business requirements into robust data models (Facts, Dimensions, and abstraction layers).

Requirements

  • Deep expertise in Databricks (Delta Lake, Unity Catalog, Workflows/Jobs, and Pipelines) and orchestration tools like Azure Data Factory or Airflow.
  • Experience in query optimization, Spark tuning, and handling large volumes of data.
  • Proven ability to navigate high-uncertainty environments, refining processes and translating executive needs into tangible technical solutions.
  • Familiarity with development best practices (GitFlow, clean code, modularization, and design patterns).
  • Strong communication skills and the ability to work collaboratively in a remote setting.

Nice to Have

  • Experience with machine learning frameworks and data analytics tools.
  • Knowledge of cloud security best practices.
  • Familiarity with Agile methodologies.

What We Offer

  • Health and dental insurance.
  • Meal and food vouchers.
  • Childcare assistance.
  • Extended parental leave.
  • Partnerships with gyms and wellness professionals through Wellhub (Gympass).
  • Profit-sharing program.
  • Life insurance.
  • Continuous learning platform (CI&T University).
  • Discount club and online health promotion platform.
Language Requirements
EnglishB2
BasicIntermediateAdvancedNative
Why This Job8.5 of 10

This remote Mid-Senior Data Developer role at CI&T offers a unique opportunity to work on cutting-edge data architecture projects while enjoying extensive benefits and a supportive work environment.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

Proficient in Python and PySpark, with hands-on experience in building data pipelines and ETL processes, ensuring data integrity and performance optimization in cloud environments.

Strong understanding of Azure Data Factory and Databricks for managing and orchestrating data workflows, with a focus on remote collaboration and agile methodologies to adapt quickly to changing project requirements.

Experience with SQL for data analysis and transformation, coupled with a mindset for continuous improvement and innovation in data engineering practices, particularly in migrating legacy systems to cloud architectures.

Learning Resources

Python for Data Science Handbookguide

Career Path

Mid-Senior Data Developer(Now)Data Engineering Lead(1-2 years)Data Architect(3-5 years)

Market Overview

Market Size 2024
$20.5B
Annual Growth
12.5%
AI Adoption
45%
Investment
+50%
Labour Demand
+30%
Avg Salary
$95K

Skills & Requirements

Required
PythonPySparkSQL
Growing in Demand
Machine LearningData Visualization (e.g., Tableau, Power BI)Cloud Computing (AWS, Google Cloud)
Declining
Traditional ETL Tools (e.g., Informatica)R Programming

Domain Trends

Rise of Data Engineering
Data engineering roles are expected to grow by 25% through 2025 as organizations increasingly rely on data-driven decision-making.
Increased Cloud Adoption
Over 70% of organizations are migrating to cloud-based data solutions, emphasizing skills in Azure Data Factory and Databricks.
Integration of AI in Data Processing
AI-driven data analytics tools are projected to see a growth of 40% in adoption, enhancing the importance of Python and PySpark in data workflows.

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