About the role
oles & Responsibilities:
- Create and maintain optimal data pipeline architecture
- Build data pipelines that transform raw, unstructured data into formats that data analyst can use to for analysis
- Assemble large, complex data sets that meet functional / non-functional business requirements
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and delivery of data from a wide variety of data sources using SQL and AWS ‘Big Data’ technologies
- Work with stakeholders including the Executive, Product, and program teams to assist with data-related technical issues and support their data infrastructure needs.
- Work with data and analytics experts to strive for greater functionality in our data systems
- Develops and maintains scalable data pipelines and builds out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using HQL and 'Big Data' technologies
- Implements processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it
- Write unit/integration tests, contribute to engineering wiki, and document work
- Performs root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
Who You Are:
- You’re passionate about Data and building efficient data pipelines
- You have excellent listening skills and empathetic to others
- You believe in simple and elegant solutions and give paramount importance to quality
- You have a track record of building fast, reliable, and high-quality data pipelines
- Passionate with good understanding of data, with a focus on having fun, while delivering incredible business results
- Must have skills:
- A Data Engineer with 5+ years of relevant experience who is excited to apply their current skills and to grow their knowledge base.
- A Data Engineer who has attained a degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
- Has experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra
- Experience with data pipeline and workflow management tools
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with object-oriented/object function scripting languages: Python, Java, Scala, etc.
- Experience with Airflow
- Experience in AWS/Spark/Python development
- Experience in GIT, JIRA, Jenkins, Shell scripting
- Familiar with Agile methodology, test-driven development, source control management and automated testing
- Build processes supporting data transformation, data structures, metadata, dependencies and workload management
- Experience supporting and working with cross-functional teams in a dynamic environment
Nice to have skills:
- Experience with stream-processing systems: Storm, Spark-Streaming, etc. is a plus
- Experience with Snowflake