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Senior Data Engineer
Há 1 mês
Sobre o nosso cliente
Our client is committed to leveraging data and analytics to improve services and drive innovation in the financial services industry. This is a 100+ people department focused on digital, AI and innovation.
Descrição
- Act as the primary technical point of contact for Product Owner and business stakeholders.
- Take ownership of data engineering responsibilities within projects.
- Lead technical architecture, design sessions, and solution breakdowns.
- Mentor and guide junior Data Engineers.
- Design and implement batch and real-time data ingestion pipelines using Databricks (PySpark) and DBT.
- Clean, transform, and optimize data for analytics and machine learning.
- Define and optimize database schemas, storage formats (Parquet, Delta Lake), and indexing strategies.
- Collaborate with data analysts, data scientists, and platform teams to ensure best practices and integration.
- Implement security, compliance, and role-based access controls in Azure environments.
- Configure and maintain Azure cloud infrastructure (Data Lake, Blob Storage, Data Factory, Databricks).
- Create documentation, support onboarding, and promote best practices.
- Monitor, troubleshoot, and continuously improve workflows and systems.
- Stay up to date with advancements in data engineering technologies and propose optimizations.
- Demonstrate initiative by proactively taking ownership of projects and tasks; deliver consistent, high-quality work; foster empathy and accountability within the team.
- Explain complex technical concepts clearly to non-technical stakeholders; actively listen and consider feedback; produce clear documentation; build strong relationships across teams; embrace constructive criticism for improvement.
- Apply analytical thinking to break down complex problems; use creativity to develop innovative solutions; show resilience when facing challenges and setbacks.
Perfil ideal
- Strong Python skills, including data manipulation libraries (e.g., Pandas) and database interfacing.
- Knowledge of Python ecosystem tools (e.g., poetry, venv) and best software engineering practices (design patterns, testing, clean code).
- Advanced SQL expertise for querying, transformation, and optimization.
- Ability to design scalable, robust data pipelines and efficient database schemas.
- Experience with dimensional modeling, 3NF, Data Vault, and ETL design.
- Proficiency with DBT for data modeling and transformation.
- Hands-on experience with Azure services (Data Lake, Data Factory, Blob Storage, SQL Database).
- Proficiency in Azure Databricks (Spark jobs, clusters, secret scopes, Unity Catalog).
- Strong PySpark skills and knowledge of Delta Lake for reliable data lakes.
- Familiarity with relational (SQL Server) and NoSQL databases (Cosmos DB).
- Understanding of data formats (Parquet, JSON, CSV, Delta).
- Experience designing and managing data integration solutions with Azure Data Factory.
- Expertise in query tuning and pipeline optimization.
- Knowledge of encryption techniques and role-based access controls integrated with Azure AD.
- Experience with CI/CD pipelines (Azure DevOps).
- Familiarity with Infrastructure as Code (ARM templates, Terraform) and containerization (Docker, Kubernetes).
- Knowledge of Azure Monitor, Log Analytics, and debugging data pipelines.
Vantagens
- Opportunity to work in a data-driven organization.
- Engaging and supportive company culture.
