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As a Senior Data Engineer, you'll design and maintain data pipelines, ensure data quality and governance, and collaborate with teams to implement solutions.
Top Skills:
AirflowAws Data & AnalyticsEmrGlueHudiIcebergLakeformationPysparkTrino
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Design and build secure and reliable microservices for managing data collection on millions of vehicles. Lead cloud application development and support cross-functional collaboration.
Top Skills:
Cloud ApplicationsJavaMicroservicesSpring Boot
Retail • Energy • Utilities
The Senior Data Engineer designs, develops, and manages data transformation pipelines in a big data environment while mentoring juniors and collaborating with teams.
Top Skills:
SparkDbtEvent HubsGitHadoopKafkaMicrosoft HdinsightPython
We are seeking a skilled and motivated Python and Database Developer to join our dynamic technology team. The ideal candidate will possess strong programming skills in Python, a solid understanding of database systems, and the ability to design, develop, and maintain efficient and scalable applications. This role involves working on a variety of projects, including data processing pipelines, web applications, and database integrations.
Responsibilities and Duties
Required Skills and Qualifications:
Responsibilities and Duties
- Data Engineering Leadership: Lead the design and development of data pipelines for ingestion, transformation, and loading of data from various sources (databases, APIs, streaming platforms) into our data warehouse/lake, ensuring seamless data flow and accessibility.
- Develop data models that support business requirements and analytical needs.
- Optimize data models for query performance and data accessibility.
- Ensure data models are well-documented and aligned with industry best practices.
- Database Optimization: Write optimized and maintainable SQL queries and leverage SQLAlchemy for efficient database interaction, ensuring high performance and data accuracy.
- Data Quality Assurance: Implement robust data quality checks and monitoring systems to ensure data integrity and accuracy, proactively identifying and resolving data issues.
- Data Governance Contribution: Contribute to the design and implementation of data governance policies and procedures, ensuring compliance with regulatory requirements and internal standards.
- Cross-Functional Collaboration: Collaborate closely with Data Scientists, Data Analysts, and business stakeholders to translate complex business requirements into efficient and impactful data solutions.
- Technology Innovation: Continuously research and implement new technologies and best practices to improve the efficiency, scalability, and resilience of our data platform.
- Cloud Deployment & Monitoring: Take ownership of the deployment and monitoring of data pipelines and related infrastructure on cloud platforms such as OpenShift, ECS, or Kubernetes, ensuring optimal performance and reliability.
- Operational Excellence: Ability to occasionally work a non-standard shift, including nights and/or weekends, and/or have on-call responsibilities to support critical data operations.
Required Skills and Qualifications:
- Education: Bachelor's degree in Computer Science, Software Engineering, or a related field.
- Experience: 6+ years of hands-on experience in a Data Engineering role
- Proven experience with database design, development, and administration.
- Data Visualization: Experience with data visualization tools and techniques for presenting data insights effectively.
- Agile Methodologies: Familiarity with agile development methodologies and experience working in agile teams.
- Strong proficiency in Python (version 3.6+), with experience in Python packaging and shared libraries like Pandas and NumPy.
- API Development: Experience implementing REST APIs in Python using microframeworks like Flask.
- Extensive experience working with relational databases, writing complex SQL, and optimizing queries for performance.
- Proven expertise with SQLAlchemy or similar ORM libraries for efficient database interaction.
- Experience with workflow management tools like Airflow (experience with PySpark or PyFlink is a major plus).
- Data Warehousing Knowledge: Solid understanding of data warehousing concepts and experience working with large datasets, including data modeling and ETL processes.
- Leadership & Mentorship: Ability to guide and mentor junior developers, fostering a collaborative team environment and promoting professional growth.
- Communication Skills: Strong communication skills, both written and verbal, with the ability to explain complex technical concepts to both technical and non-technical audiences.
- DevOps Practices: Experience working in a Continuous Integration and Continuous Delivery environment and familiarity with tools like Jenkins, TeamCity, SonarQube, OpenShift, ECS, or Kubernetes.
- Software Engineering Principles: Proficient in industry-standard best practices such as Design Patterns, Coding Standards, Coding modularity, and Prototyping.
- Design, develop, and maintain database schemas and models.
- Write and optimize SQL queries for data retrieval, manipulation, and reporting.
- Communicate technical concepts and solutions effectively to both technical and non-technical audiences.
- Provide technical support and troubleshooting for production systems.
- Stay up-to-date with the latest trends and technologies in Python development, database systems, and data engineering.
- Evaluate and recommend new tools and technologies to improve development efficiency and product quality.
- Contribute to the continuous improvement of development processes and practices.
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Job Family Group:
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Job Family:
Applications Development------------------------------------------------------
Time Type:
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