Senior Analytics Engineer

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banco BV

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1993

💸 Finance

🏦 Banking

💳 Fintech

💰 Debt Financing on 2022-07

Finance • Banking • Fintech

banco BV is a financial institution that offers a wide range of banking services to both individual consumers and businesses. It provides personal and corporate accounts, credit cards, loans, financing for vehicles and solar energy, insurance solutions, and investment services. The bank also focuses on digital solutions, such as mobile banking apps and open finance initiatives, to enhance accessibility and customer experience. As a versatile financial entity, banco BV caters to both private and corporate clients, providing comprehensive banking and financial services.

📋 Description

• Develop and maintain data ingestion and transformation pipelines; • Work with Lakehouse architectures; • Work in GCP and Databricks environments; • Create and evolve data structures in BigQuery and Delta Lake; • Support the definition and application of dimensional and relational modeling (Star Schema, Snowflake, etc.); • Ensure data quality, consistency, and security; • Support performance and cloud cost monitoring activities; • Collaborate with business units and data teams.

🎯 Requirements

• Experience with Cloud platforms (GCP) • Strong expertise in BigQuery: • Data modeling • Query optimization • Performance tuning • Experience with GCP data services: • Dataflow, Pub/Sub, and Cloud Storage (a plus) • Strong knowledge of advanced SQL • Experience with dbt (Data Build Tool) for: • Data transformation • Versioning • Implementing analytical best practices • Experience with Databricks: • Developing data pipelines using Spark (PySpark/SQL) • Modeling and transformation in a Lakehouse environment • Workload orchestration and performance optimization • Integration with modern data architectures (Delta Lake, medallion architecture) • Knowledge of data ingestion: • Batch and streaming • Experience with data transformation and modeling: • ELT/ETL • Dimensional modeling and/or Data Vault • Knowledge of data governance: • Data catalog • Data lineage • Access and security policies • Experience with data quality: • Automated testing (dbt tests or similar) • Monitoring and observability of pipelines • Experience migrating legacy systems to the Cloud • Knowledge of: • Code versioning (Git) • CI/CD practices applied to data pipelines • Familiarity with modern concepts: • Data Products • Data Mesh (a plus)