Senior Data Engineer

We are seeking a highly skilled and motivated Data Engineer to join our dynamic team. The ideal candidate will be responsible for designing, building, and maintaining our data-driven infrastructure.

You will work closely with data scientists, analysts, and other stakeholders to ensure that our data is accessible, reliable, and ready for analysis.

Your work will be crucial in enabling our organization to make data-informed decisions and optimize performance.

Responsibilities

As a Data Engineer, you will be tasked with a variety of responsibilities, including:

• Develop and Maintain Data Pipelines: Design, construct, install, test, and maintain highly scalable data management systems.
• ETL Processes: Implement and manage ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes to move and transform data between various systems.
• Data Modeling and Warehousing: Build and maintain unified catalog, data warehouse, and/or data lake solutions, creating and managing table schemas to organize and store data effectively.
• Data Quality and Integrity: Ensure data quality and reliability by creating data validation methods and implementing data governance and security policies.
• Collaboration: Work with data scientists, analysts, and business leaders to understand data needs and deliver solutions that align with company objectives.
• Automation: Write scripts and use orchestration tools to automate repetitive tasks and data workflows.
• System Monitoring and Optimization: Monitor the performance of data systems and optimize them for speed, reliability, and cost-effectiveness.

To be successful in this role, you should have the following qualifications:

• Education: Bachelor's degree in Computer Science, Engineering, or a related field.
• Experience: Proven experience as a Data Engineer or in a similar role.
• Programming Skills: Proficiency in SQL and at least one of the following programming languages: Python, Java, or Scala.
• Database Knowledge: Strong experience with both relational (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• Big Data Technologies: Hands-on experience with big data tools such as Apache Spark, Hadoop, or Kafka.
• Cloud Platforms: Familiarity with cloud services like AWS, Azure, or Google Cloud.
• ETL Tools: Experience with ETL frameworks and tools such as Talend, Informatica, or AWS Glue.

Preferred Qualifications

The following qualifications are not required but will be considered a strong plus:

• Advanced Degree: Master's degree in a related field.
• Certifications: Professional certifications such as the AWS Certified, Google Cloud Certified Professional Data Engineer, IBM Certified Data Engineer, or Microsoft Certified: Azure Data Engineer Associate.
• Data Modeling: In-depth knowledge of data modeling techniques, including star and snowflake schemas.
• Containerization and Orchestration: Experience with Docker and Kubernetes.
• CI/CD: Understanding of CI/CD principles and experience with related tools (e.g., Jenkins, GitLab CI).
• Communication Skills: Excellent communication and collaboration skills to work effectively with various teams.

Pulled from the full job description

• Referral program
• Professional development assistance
• Parental leave
• 401(k)
• Health insurance
• 401(k) matching
• Paid time off, * 401(k)
• 401(k) matching
• Dental insurance
• Flexible schedule
• Health insurance
• Life insurance
• Paid time off
• Parental leave
• Professional development assistance
• Referral program
• Vision insurance