Senior Data Engineer
ByriderAbout the role
Leading national automotive sub-prime consumer finance company has a Senior Data Engineer career opportunity open at the national headquarters in Carmel, Indiana. This is a hybrid position that requires 3 days in the office each week. We offer a competitive starting pay based on experience, great benefits and a newly remodeled corporate office.
Job Summary for Senior Data Engineer:
We seek a highly skilled and experienced Senior Data Engineer to join our dynamic team. As a Senior Data Engineer, you will play a critical role in designing, developing, and maintaining our data infrastructure, ensuring the availability, reliability, and performance of our data systems. You will drive the data engineering initiatives and collaborate closely with cross-functional teams to support data-driven decision-making within the organization. You must also be skilled at finding solutions to problems while keeping the environment well-structured, stable, and secure. This position reports to the Director of Solutions Engineering.
Specific Responsibilities for Senior Data Engineer:
● Data Architecture: Lead the design and development of complex data pipelines, data models, and data integration solutions that meet business requirements and performance standards
● Data Ingestion: Architect and oversee the development of efficient and scalable data ingestion processes from various sources, including databases, APIs, and external data providers (AWS Redshift, AWS DynamoDB, AWS S3, MS SQL, etc.)
● Data Transformation: Develop advanced data transformation pipelines and ETL processes to convert raw data into structured and meaningful formats
● Data Quality: Establish and enforce best practices for data quality, validation, cleaning, and error handling
● Data Storage: Manage and optimize data storage solutions, including databases, data lakes, and cloud storage services
● Data Security: Implement advanced data security measures and access controls to protect sensitive data
● Performance Optimization: Continuously monitor and optimize the performance of data pipelines and databases, implementing best practices to ensure efficient data processing
● Collaboration: Collaborate closely with leadership, analysts, and business stakeholders to understand their data requirements and deliver advanced data solutions that meet their evolving needs
● Innovation: Stay at the forefront of emerging data engineering technologies, industry trends, and best practices, and drive innovation within the data engineering domain
● Documentation: Maintain comprehensive documentation of data pipelines, data models, and processes, and ensure knowledge sharing within the team
Products and Stacks for Senior Data Engineer:
Languages
● C#
● Python
● TSQL
● Java
● Scala
Frameworks
● .Net Core
● .Net Framework
● ASP .NET
Database
● MS SQL
● DynamoDB
● Redshift
● Postgresql
Amazon Web Services
● ECS
● Cloudwatch
● Lambda
● S3
● Secrets
● DynamoDB
● API Gateway
● SNS
● SQS
● SES
● CloudFormation
● Glue
Azure Cloud Services
● Service Fabric Clusters
● Service Bus
● App Services
● Application Insights
● Key Vaults
● Databricks
● Function Apps
Tools and Platforms
● Docker
● Bitbucket
● Azure Devops
● Jira
● Confluence
● Lucidspark
● Looker
Skills of Senior Data Engineer:
● Proven experience as a Senior Data Engineer, with a strong understanding of information data security and data access controls
● Proficiency in programming languages such as Python, Java, or Scala
● Strong SQL skills and deep experience with database technologies (e.g., SQL, NoSQL)
● Expertise in data warehousing and ETL tools (e.g., Kodda, AWS Glue)
● Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization (e.g., Docker, Kubernetes)
● Extensive knowledge of data modeling techniques and data warehouse design
● Excellent problem-solving and communication skills
● Ability to work collaboratively in a team, adapt to a fast-paced, evolving environment, and work individually to accomplish goals
● Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization (e.g., Docker, Kubernetes)
● Familiarity w
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