• Job Title : Data Engineer
• Location : Dallas/ Chicago / Open to remote .
• Experience : 5 plus years of Relevant experience 
• Immediate Hiring 

Essential Job Functions: 

• Create, automate, and maintain data pipelines. Assemble complex data sets that meet business requirements.
• Extract, transform, and load data from a variety of data sources using SQL and big data tools and technologies.
• Identify, design, and implement internal process improvement including automating manual processes, optimizing data delivery, re-designing infrastructure for greater reliability and performance.
• Write and optimize queries, write lambda functions, perform source to target mapping and data modeling.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work as a member of the data engineering chapter on a development squad to deliver product features and resolve data related technical issues.
• Work as a member of the data management center of excellence on data quality projects.
• Work with information security to keep our data secure.
• Work with data architects, database administrators, and data engineers to continually improve our data systems.
• Work with IT operations to resolve data related technical issues and respond to data related major incidents.
• Create data tools to assist data analysts and data scientists in building and optimizing our product into an innovative industry leader.
• Troubleshoot operations and database issues for internal and external customers.
• Perform incident resolution and root cause analysis of critical outages. Implement solutions to systematic failures. Provide on-call support, including after hours.
• Assist with documentation of the environments that support our products.
• Other duties as assigned. 

Position Requirements: 

• Bachelor's degree or equivalent professional experience required; Computer Science or Engineering preferred.
• Strong experience in SQL and Python.
• Experience with relational SQL and NoSQL Databases; MS SQL, PostgreSQL, Snowflake, MongoDB, MySQL, MariaDB, Elastic stack.
• Experience building and optimizing reliable, idempotent data pipelines (streaming or batch) using ETL tools such as Matillion, Apache NiFi, Kafka and Spark.
• A successful history applying software engineering principles to build data infrastructure tools/libraries to automate and scale data pipelines.
• Understanding of applying logging and metrics to monitor and detect data pipeline performance issues.
• Experience with Snowflake and solid understanding of Data warehousing theory and concepts. 
• Working knowledge of data modeling and source to target mapping with a demonstrated understanding of data schema design and indexes, when to apply fact-based vs. time-based vs. relational and when to apply NoSQL approaches such as key-value, document, and column data stores.
• Understanding of Statistical and Machine Learning (ML) terminology with experience deploying and monitoring ML-models in a production environment.
• Experience working in a modern cloud based environment a plus; Azure, AWS, Docker, Kubernetes. Data Warehouse
• Experience with Linux.
• Familiarity with Kubernetes, Lambda functions, Cloud Watch, SNS, S3, Glacier.