This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Pessoa Engenheira de Dados Analytics Pleno based in Brazil.
This is an opportunity for a mid-level Data Engineer to help build and evolve modern, scalable data platforms that support critical business decisions. You’ll work across the full data lifecycle, from ingestion and transformation to integration, modeling, and analytics consumption. The role combines hands-on development in Python and PySpark with large-scale data processing and pipeline engineering. You’ll contribute to modernization initiatives, including the migration of legacy solutions toward more scalable architectures. The environment values automation, observability, data quality, and continuous improvement. You’ll collaborate with multiple teams to turn complex data requirements into reliable and actionable solutions.
Accountabilities:
- Contribute to the definition, evolution, and ongoing support of the data platform, helping ensure reliability, scalability, and maintainability.
- Participate in data modernization initiatives and migration of legacy solutions to more scalable and efficient architectures.
- Develop, maintain, and enhance data pipelines using Python and Spark (PySpark).
- Build solutions for data ingestion, transformation, integration, processing, and delivery for analytical and operational use cases.
- Process and integrate large volumes of data from diverse sources and formats, including Parquet, JSON, CSV, TXT, relational databases, and Delta Tables.
- Monitor production data environments, identify issues, troubleshoot pipelines and integrations, and implement sustainable solutions.
- Optimize pipelines, queries, and data processes to improve performance, reliability, and scalability.
- Promote best practices in data engineering, data quality, observability, automation, and operational excellence.
- Collaborate with business and technical teams to understand functional and non-functional requirements and translate them into data solutions that support decision-making.
- Contribute to projects involving BI, Big Data, Analytics, data modeling, and large-scale data integration.
Requirements
- Bachelor’s degree or equivalent higher education qualification.
- Solid professional experience in data engineering, including the development and maintenance of data pipelines.
- Strong proficiency in Python and Spark/PySpark for data processing and engineering.
- Experience with ETL/ELT tools and data pipeline technologies such as Airbyte, dbt, Azure Data Factory, AWS Glue, Fivetran, Synapse Pipelines, Google Dataflow, Apache NiFi, Talend, or similar platforms.
- Strong knowledge of Git and modern version-control practices.
- Experience working with different data sources and formats, as well as integrating and processing large volumes of data.
- Experience with data modeling, including relational and dimensional modeling and Data Warehouse structures.
- Experience managing and working across multiple databases.
- Background in BI, Big Data, Analytics, or related data projects.
- Familiarity with messaging technologies such as RabbitMQ, Kafka, or similar tools.
- Strong analytical and problem-solving skills, with the ability to understand business rules and identify opportunities for continuous improvement.
- Adaptability and willingness to work in changing environments, with a collaborative and solution-oriented mindset.
- Knowledge of data integration, pipeline monitoring, troubleshooting, and performance optimization.
Nice-to-have skills:
- Hands-on experience with Databricks in production environments.
- Knowledge of Lakehouse architecture and Delta Lake.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Experience automating processes and orchestrating data pipelines.
- Knowledge of observability, monitoring, and performance optimization for data pipelines.
- Familiarity with DataOps and modern data engineering best practices.
- Cloud, Data, or Databricks certifications.
Benefits
- 🌍 Remote or hybrid work, available to professionals residing in Brazil.
- ⏰ Flexible working hours to support work-life balance.
- 🏥 Health insurance, dental insurance, and life insurance, with coverage extendable to eligible dependents.
- 💊 Medication assistance, also available for children.
- 🍔 Flexible meal and food allowance.
- 🚍 Transportation allowance or parking assistance for employees living near company offices.
- 🏋️ Wellhub and TotalPass access to support health and wellness.
- 🏖️ Birthday day off, with the flexibility to choose the day.
- 🧸 Parental support program for new mothers and fathers.
- 👨🎓 Professional development support through external training and learning opportunities.
- 🏫 Childcare assistance.
- 👶 Extended parental leave, including 6 months for mothers and 30 days for fathers.
- 💵 Employee referral bonuses and additional recognition programs.
- Opportunities to work in a collaborative environment focused on continuous learning, innovation, and career development.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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