Senior Data Engineer
Nomis is looking for an outstanding data expert to join our team. The Data Engineer will collaborate closely with our client services team to process critical data while working to power advanced analytics and enable the integration of data science across the company.
You are ready to be flexible and nimble in your work, from constructing ETL pipelines for customer delivery to participating in exploratory data analysis with our Analytics team.
Who We Are & What We Build
We partner with Banks and FinTechs on their journey to best-in-class pricing technology and analytics so that they deliver more value to their customers, employees and shareholders.
Our top-notch people, proven technology, and innovative analytics are tackling big data challenges at banks and lenders every day.
We deliver market-leading cloud-based Pricing & Profitability Management solutions and insights for the Banking & Financial Services industry leveraging cutting-edge behavioral data science.
We are a Blue Chip venture-backed company with the vision to transform the consumer banking landscape.
Establish and maintain big data processing platformBuild data management applications and microservices on AWSDesign and implement Hive / Greenplum / RedShift distributed data warehouses and standard schemasDesign, develop, maintain cross-platform ETL processes and MapReduce / Hive / Spark data processing workflowsManage and maintain reference data securely on S3 and other storage systems
Support client services teams byManage, customize, and automate cloud-based (AWS) data processing supporting multiple clientsAdministration of relational databases, capacity plans, infrastructure and storage designOversee and execute data migration from existing data storesApplication / implementation of custom analytics applications and datasetsDevelop code standards, guidelines, and automated test suites to ensure highest data quality and integrity
Desired Skills and Requirement
Experience with building distributed systems, query processing, and the Hadoop ecosystem
Understanding of Data warehousing - architect and design data warehouse
Expertise with data schema - logical and physical data modeling
Knowledge of ETL processes and tools
Experience with AWS or a major cloud platform such as GCP
Proficiency in : Python, SQL, Java
Strong pluses :
Experience of Business Intelligence tooling such as Tableau
Experience with data mining techniques and analytics functions
Predictive analytics experience is a PLUS
Experience with Spark 2, Apache Airflow and other modern data engineering tooling a strong plus
Experience with streaming architectures and MPP databases such as Greenplum a strong plus
Up-to-date with the open-source community w.r.t. data engineering
Experience with the following services in AWS a strong plus : EMR, Lambda, Kinesis, Firehose, S3
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