🕒 9 days ago
Engenheiro(a) de Dados responsável por desenvolver e manter pipelines escaláveis e seguros, integrar fontes de dados e traduzir necessidades de negócio em soluções de dados no ecossistema AWS.
Technical Data Engineer -Databricks
🕒 3 days ago
PythonPysparkAdvanced SQLDatabricks Lakehouse Platform
📜 Description
- Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and SQL.
- Integrate data from databases, Amazon S3, files, and REST APIs; support data ingestion and export.
- Build pipelines with Unity Catalog and implement business logic, transformations, and dimensional data models.
- Create, schedule, monitor, and optimize Databricks Jobs and Workflows; manage Delta Lake tables using Medallion Architecture.
- Ensure data quality with validations, error handling, logging, and monitoring; tune Spark workloads for performance and reliability.
- Collaborate with cross-functional teams to deliver production-ready data solutions.
🛠️ Requirements
- Hands-on experience with the Databricks Lakehouse Platform.
- Experience integrating with REST APIs for data ingestion and data export.
- Strong knowledge of ETL/ELT development, batch processing, incremental loading, and data transformation.
- Experience with data modeling (Star Schema, Snowflake Schema, Fact & Dimension tables, SCD concepts).
- Understanding of data warehousing concepts and best practices.
- Experience working with structured and semi-structured data (CSV, JSON, Parquet, Delta).
- Knowledge of partitioning, file optimization, Spark performance tuning, and query optimization.
- Experience with Git and CI/CD best practices
- Experience with Auto Loader, Spark Declarative pipelines, Kafka, Airflow, or dbt is a plus.
- Databricks certification is an added advantage.
✨ Benefits
- Competitive salary
- Strong insurance package
- Learning and development resources
Full job description
Position Overview
We are looking for a Data Engineer with hands-on experience in building scalable data pipelines and data engineering solutions on the Databricks Lakehouse Platform. The ideal candidate should have strong expertise in Python, PySpark, SQL, Databricks, AWS, and REST API integrations for data ingestion, managing large volumes of data, and data export
ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.
Job Responsibilities:
Design, develop, and maintain scalable ETL/ELT pipelines using Databricks,
PySpark, and SQL.
● Integrate data from multiple sources, including databases, Amazon S3, files, and REST APIs.
● Build data pipelines with Databricks Unity Catalog.
● Implement business logic, data transformations, and dimensional data models.
● Create, schedule, monitor, and optimize Databricks Jobs and Workflows.
● Design and manage Delta Lake tables using Medallion Architecture (Bronze, Silver,Gold).
● Ensure data quality through validations, error handling, logging, and monitoring.
● Optimize Spark workloads for performance, scalability, and reliability.
● Collaborate with cross-functional teams to deliver production-ready data solutions.
PySpark, and SQL.
● Integrate data from multiple sources, including databases, Amazon S3, files, and REST APIs.
● Build data pipelines with Databricks Unity Catalog.
● Implement business logic, data transformations, and dimensional data models.
● Create, schedule, monitor, and optimize Databricks Jobs and Workflows.
● Design and manage Delta Lake tables using Medallion Architecture (Bronze, Silver,Gold).
● Ensure data quality through validations, error handling, logging, and monitoring.
● Optimize Spark workloads for performance, scalability, and reliability.
● Collaborate with cross-functional teams to deliver production-ready data solutions.
Basic Qualification:
Strong expertise in Python, PySpark, and Advanced SQL.
● Hands-on experience with the Databricks Lakehouse Platform.
● Good understanding of Unity Catalog, Delta Lake, Databricks Workflows/Jobs,
Clusters, Notebooks, Repos, and Medallion Architecture.
● Experience integrating with REST APIs for data ingestion and data export.
● Strong knowledge of ETL/ELT development, batch processing, incremental loading, and data transformation.
● Hands-on experience with the Databricks Lakehouse Platform.
● Good understanding of Unity Catalog, Delta Lake, Databricks Workflows/Jobs,
Clusters, Notebooks, Repos, and Medallion Architecture.
● Experience integrating with REST APIs for data ingestion and data export.
● Strong knowledge of ETL/ELT development, batch processing, incremental loading, and data transformation.
Data Governance experience would be an added advantage.
● Experience with data modeling (Star Schema, Snowflake Schema, Fact & Dimension tables, SCD concepts).
● Understanding of data warehousing concepts and best practices.
● Experience working with structured and semi-structured data (CSV, JSON, Parquet, Delta).
● Knowledge of partitioning, file optimization, Spark performance tuning, and query optimization.
● Experience with Git and CI/CD best practices
● Experience with data modeling (Star Schema, Snowflake Schema, Fact & Dimension tables, SCD concepts).
● Understanding of data warehousing concepts and best practices.
● Experience working with structured and semi-structured data (CSV, JSON, Parquet, Delta).
● Knowledge of partitioning, file optimization, Spark performance tuning, and query optimization.
● Experience with Git and CI/CD best practices
Preferred Qualifications:
4+ years of experience in Data Engineering with 2+ years of hands-on Databricks
experience. Data Governance experience would be an added advantage.
● Experience with Auto Loader, Spark Declarative pipelines, Kafka, Airflow, or dbt is a plus.
● Databricks certification is an added advantage.
experience. Data Governance experience would be an added advantage.
● Experience with Auto Loader, Spark Declarative pipelines, Kafka, Airflow, or dbt is a plus.
● Databricks certification is an added advantage.
Similar jobs
Search more Data Engineer jobs
🕒 3 days ago
As a Data Engineer II, you will build and maintain data pipelines, implement data models, and ensure data quality while collaborating with cross-functional teams.
🕒 4 days ago
Build and maintain data pipelines, warehouses, APIs, and services while supporting reporting and deploying machine-learning models that improve user experiences and inform business decisions.
Data Integration Developer (Informatica CDI)
🕒 4 days ago
NucleusTeq👥 201 - 500 employees🏢 Information Technology And Services
🕒 4 days ago
Design, build, test, and maintain Informatica CDI data pipelines that integrate and transform data across cloud and on-premise platforms for enterprise analytics and reporting.
Data Engineer in FCP DVR team – GCP migration project (temporary contract)
🕒 7 days ago
Seb👥 10,000+ employees🏢 Banking
🕒 7 days ago
Lead part of the FCP Data Visualization and Reporting team’s migration from on-premises to GCP, refactoring data pipelines and coordinating technical solutions, requirements, estimates, and project updates.