Data Platform Engineer

Data Platform Engineer – Specializing in Data Engineering

We are seeking an accomplished Data Platform Engineer to spearhead the design, development, and maintenance of a robust, self-service data platform.

This highly skilled professional will oversee the creation of end-to-end data pipelines that empower Data Analysts and Data Scientists to derive actionable insights and drive strategic decision-making.

1. Design and build high-performance data platforms that align with business objectives, integrate seamlessly with product solutions, and foster analytical innovation;
2. Create, edit, and manage data pipelines, ensuring they adhere to business logic, optimize data quality, and provide efficient data aggregation and transformation;
3. Develop and implement data modeling and transformation workflows, enabling clear and accessible data abstractions;
4. Oversee the entire code development lifecycle, including monitoring, deployment, documentation, performance optimization, security measures, adding metrics, alarms, and compliance with service-level objectives (SLOs);
5. Investigate inconsistencies, identify the source of differences, and troubleshoot data-related issues;
6. Enable cross-functional teams to access and utilize data effectively through self-service tools and well-structured datasets;
7. Collaborate with stakeholders to understand their primary needs while maintaining a holistic view of the problem and proposing scalable, incremental solutions;
8. Conduct proof-of-concept studies and benchmarks to determine the most effective tools for specific problems and decide whether to leverage off-the-shelf solutions or develop them in-house;
9. Contribute to defining the organization's strategic vision by bridging team and service boundaries to solve complex problems;
10. Advocate for data analytics and engineering best practices within the organization and promote a data-driven culture;
11. Establish expertise in technical concepts, tools, and coding best practices, serving as a reference point within the field;

1. A minimum of 7 years of experience in Data Engineering roles;
2. Specialization in Big Data technologies, including Spark, Hadoop, Hive, MapReduce, and proficiency in multiple programming languages such as Python and YAML;
3. Familiarity with Airflow, Spark, AWS, and Databricks;
4. A strong foundation in software engineering principles, with experience working on data-centric systems;
5. Experience with columnar storage solutions and/or data lakehouse concepts;
6. Proficiency in Python or other main programming languages and a passion for writing clean, maintainable code;
7. Strong knowledge of SQL query optimization techniques;
8. Experience in building multidimensional data models, including Star and Snowflake schema;
9. Understanding of the data lifecycle and related concepts like lineage, governance, privacy, retention, anonymization, etc.;
10. Familiarity with infrastructure areas such as containers, orchestration (Kubernetes, ECS), CI/CD strategies, infrastructure as code (Terraform), observability (Prometheus, Grafana), and others;
11. Proficiency in English, as code, documentation, tools, and materials are often structured in this language;
12. Excellent communication skills, with the ability to proactively share and collaborate with both technical and non-technical stakeholders to translate business needs into scalable data solutions;
13. Experience as a tech/project lead or similar;
14. Curiosity, attention to detail, and the ability to thrive in a fast-paced, data-driven environment;
15. Prior experience in building large-scale data platforms for big data sets and teams using Big Data technologies like Spark, Trino, Hive, Atlas, Ranger, etc.;
16. Experience in developing semantic layers;

1. Competitive salary package;
2. Bonus;
3. Meal allowance;
4. Health plan;
5. Dental plan (optional);
6. Life insurance;
7. Daycare subsidy;
8. Subsidy to sports practicing;
9. Extended maternity and paternity leave;
10. Reserved room for breast-feeding;
11. Educational discounts;