Senior Software Developer

Who you are

• 7+ years of software development experience at multiple capacities
• 2+ years of experience in big data technologies (we use Airflow, EMR/Spark, Snowflake, Hadoop/Hive)
• Experience with data streaming (we use Kinesis/Kafka)
• Proficiency in programming languages (we use Python, Java/Scala)
• Experience building RESTful APIs and microservices
• Experience with relational databases (we use MySQL, PostgreSQL)
• Background on cloud technologies. (we use AWS, S3/EBS, Lambda, EKS, CloudWatch)
• Familiarity with observability platforms (we use Splunk, Datadog)
• Have sound knowledge of design patterns and methodologies across multiple platforms
• Knowledge and support of modern development practices, such as Agile and Open-Source technologies
• Excellent debugging skills
• Bachelor's in computer science or equivalent
• Certifications (optional)
• AWS Certified Developer - Associate

What the job involves

• The reporting team is looking for an experienced Sr. Software Developer. You will be reporting to the Engineering Manager of Reporting Team. You will develop software solutions for complex ETL data pipelines and scalable APIs. You will work with Product Managers, Infrastructure, Business Operations, Quality Assurance and other team members to ensure that data is accessible, reliable, and well-structured for reporting
• Data Pipeline Development
• Develop data pipelines to extract, transform, and load (ETL) data from multiple sources into a centralized data repository
• Improve and refine data pipelines for efficiency, reliability, and scalability
• Monitor and troubleshoot data pipeline issues and ensure data integrity
• We use Python, Airflow, Snowflake, Hive, MySQL, Kinesis, Kafka and AWS (Amazon Web Services)
• API Development
• Develop RESTful APIs & microservices to support multiple operations
• Follow best practices for security, scaling, cost effectiveness and testing
• Create unit and integration tests
• Contribute to documentation on use of the APIs
• Problem Solving
• Resolve technical issues and bugs in applications
• Identify performance bottlenecks and improve code and databases
• Team Collaboration
• Collaborate with engineers, analysts, cross-functional teams and partners to understand data requirements and deliver relevant insights
• Performance Optimization
• Improve data processing and query performance for data retrieval and analytics
• Code Review and Documentation: Perform code review and provide constructive feedback within ethical boundaries
• Test and Quality Assurance
• Stay up to date with the latest data engineering technologies, and best practices
• Recommend new technologies for data engineering improvements
• Security and Compliance
• Ensure data security by implementing access controls, encryption, and comply with data privacy regulations