Data Engineer

• Design and build scalable data infrastructure with efficiency, reliability, and consistency to meet rapidly growing data needs
• Build the applications required for optimal extraction, cleaning, transformation, and loading data from disparate data sources and formats using the latest big data technologies
• Building ETL/ELT pipelines and work with other data infrastructure components, like Data Lakes, Data Warehouses and BI/reporting/analytics tools
• Work with various cloud services like AWS, GCP, Azure to implement highly available, horizontally scalable data processing and storage systems and automate manual processes and workflows
• Implement processes and systems to monitor data quality, to ensure data is always accurate, reliable, and available for the stakeholders and other business processes that depend on it
• Work closely with different business units and engineering teams to develop a long-term data platform architecture strategy and thus foster data-driven decision-making practices across the organization
• Help establish and maintain a high level of operational excellence in data engineering
• Evaluate, integrate, and build tools to accelerate Data Engineering, Data Science, Business Intelligence, Reporting, and Analytics as needed
• Focus on building test-driven development by writing unit/integration tests
• Contribute to design documents and engineering wiki

You will enjoy this role if you...

• Like building elegant well-architected software products with enterprise customers
• Want to learn to leverage public cloud services & cutting-edge big data technologies, like Spark, Airflow, Hadoop, Snowflake, and Redshift
• Work collaboratively as part of a close-knit team of geeks, architects, and leads

Desired Skills & Experience:

• 2+ years of data engineering or equivalent knowledge and ability
• 2+ years software engineering or equivalent knowledge and ability
• Strong proficiency in at least one of the following programming languages: Python, Scala, or Java
• Experience designing and maintaining at least one type of database (Object Store, Columnar, In-memory, Relational, Tabular, Key-Value Store, Triple-store, Tuple-store, Graph, and other related database types)
• Good understanding of star/snowflake schema designs
• Extensive experience working with big data technologies like Spark, Hadoop, Hive
• Experience building ETL/ELT pipelines and working on other data infrastructure components like BI/reporting/analytics tools
• Experience working with workflow orchestration tools like Apache Airflow, Oozie, Azkaban, NiFi, Airbyte, etc.
• Experience building production-grade data backup/restore strategies and disaster recovery solutions
• Hands-on experience with implementing batch and stream data processing applications using technologies like AWS DMS, Apache Flink, Apache Spark, AWS Kinesis, Kafka, etc.
• Knowledge of best practices in developing and deploying applications that are highly available and scalable
• Experience with or knowledge of Agile Software Development methodologies
• Excellent problem-solving and troubleshooting skills
• Process-oriented with excellent documentation skills