Middle Data Engineer at Exadel Inc (Website)

, São Paulo, Brazil -

Full Time

Start Date

Immediate

Expiry Date

13 Apr, 26

Salary

0.0

Posted On

13 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, SQL, ETL, ELT, Python, AWS, Amazon S3, Redshift, Athena, Data Warehousing, Data Lakes, BI Tools, Data Quality, Governance, Analytical Data Modeling, Git

Industry

Software Development

Description

Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. What You’ll Do Design and evolve data architectures supporting strategic indicators, goals, and engagement Build and automate ETL/ELT pipelines integrating transactional and analytical systems Develop and optimize analytical data models (Star Schema and Snowflake) Write and optimize advanced SQL (CTEs, window functions, performance tuning) Implement data processing and automation using Python Build and maintain cloud-based data platforms on AWS Work with Amazon S3, Redshift, and/or Athena to support data storage and analytics Enforce data quality, governance, and lineage across datasets Collaborate with business stakeholders to translate business needs into analytical datasets Support BI and analytics tools such as Power BI, Tableau, and Looker Ensure compliance with regulatory and governance requirements in banking and fintech environments What You’ll Bring 4+ years of experience as a Data Engineer Advanced SQL (CTEs, window functions, performance optimization) Experience with analytical data modeling (Star Schema and Snowflake) Hands-on experience building and automating ETL/ELT pipelines Strong Python skills for data processing and automation Solid experience with cloud data architectures on AWS Practical experience with Amazon S3 and Redshift and/or Athena Experience integrating transactional and analytical systems Strong background in Data Warehousing and Data Lakes Experience using Git for code versioning Strong understanding of data quality, governance, and lineage Ability to translate business requirements into reliable analytical datasets Experience with BI tools (Power BI, Tableau, Looker) Prior experience in regulated environments (banks, fintechs, LGPD) Nice to Have Experience with dbt Use of orchestration tools such as Airflow, Prefect, or Dagster Knowledge of AWS Glue Familiarity with Infrastructure as Code (Terraform) Knowledge of Lakehouse or Data Mesh architectures Experience with data streaming platforms (Kafka, Kinesis) Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable accommodations are available to enable individuals with disabilities to perform essential functions Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Responsibilities

The Middle Data Engineer will design and evolve data architectures, build and automate ETL/ELT pipelines, and develop analytical data models. They will also collaborate with business stakeholders to translate needs into analytical datasets and ensure data quality and compliance.