Engage with stakeholders to gather requirements to deliver data solutions.
Implement best practices around the data platform to automate the ingestion, transformation, and augmentation of data sources, and provide best practices for pipeline operations.
Innovate at the optimal storage guidelines around transactional, clickstream & IoT data.
Provide advice and ideas for technical solutions and improvements to data systems.
Manage a team of high-performance data engineers. Perform regular performance evaluations and share and seek feedback.
Create and maintain clear documentation on data models/schemas as well as infra-level processes.
Help troubleshoot and remediate data quality issues raised by pipeline alerts or downstream consumers.

Requirements

3 plus years of hands-on experience in Data Warehouse space - that involves dimension modeling and SQL-based (expert level) data transformation and analytics.
Hands-on experience in Big Data space - that involves designing, developing, testing, and implementing data solutions using Apache NiFi, Kafka, Spark and other Big Data ecosystem tools.
Expert in database technologies. OLTP, OLAP & MPP, alike.
Expert-level exposure to AWS and most data/analytics services.
Proven proficiency in programming languages like Java/Python.
Strong engineering mindset to build resiliency/restart ability in all the Data Platform components.
Exposure to Hortonworks solutions.
Exposure to Tableau.
Past experience working with high-energy startups.
Ability to thrive in a fast-paced start-up environment, and to manage multiple, competing priorities simultaneously
Superior analytical skills and a strong sense of ownership.
Ability to develop and organize high-quality documentation.

(ref:hirist.com)

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