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Senior Data Engineer
Chicago, IL

WHO WE ARE:

SwipeSense is a healthcare technology company, our mission is to eliminate Hospital Acquired Infections, a leading cause of death in the United States. We design and market the only comprehensive hand-hygiene compliance monitoring solution which combines sensor networks with wearable technologies to provide a complete, long-term and cost-effective solution for healthcare institutions.

SwipeSense is a high-growth venture backed company headquartered in Chicago, IL

 

WHO WE NEED: 

SwipeSense handles large-scale distributed IOT hardware networks that produce massive amounts of real-time sensor data. We’re looking for someone who is excited about designing and building with the future of big data solutions in-mind. At SwipeSense, big data means BIG data. We’re not talking about millions of data points and gigabytes of storage; we’re looking for someone who’s passionate about tackling billions of data points and terabytes of data per day with the eventual goal of handling petabyte-scale data workloads.

 

PRIMARY ROLE: Optimize and manage the current OLTP/OLAP AWS Aurora data backend and assist in the design and development of a new petabyte-scale storage and reporting solution based on the latest and greatest in big data solutions. Interface with app developers to educate and collaborate on the intricacies of building scalable data delivery. Work with analysts to enrich their data sources and ensure that SwipeSense is consistently practicing well-informed data-driven decision-making.

 

KEY RESPONSIBILITIES:

·      Maintain and optimize the current OLTP/OLAP SQL backend to get the most out of a traditional relational data backend.

·      Design and implement additional OLAP data marts to optimize reporting for our customer-facing analytics frontend.

·      Continually audit incoming data to ensure integrity and optimal performance.

·      Maintain and implement scalable ETL processes to minimize reporting latency.

·      Assist SwipeSense in moving into the future of petabyte-scale data collection and analysis by building data aggregation and computation platforms with tools such as Amazon Kinesis, Elastic Map Reduce, and Apache Spark.

 

KEY SKILLS:

·      Expert in SQL, traditional star schema data warehousing, ETL processes, and relational database performance optimization.

·      Experience building and deploying data platforms in the AWS cloud.

·      Comfort with Linux, bash, and open source tools.

·      Experience building high availability, scalable BI solutions

·      Knowledge of data backup, data security, and redundancy solutions.

 

NICE TO HAVES:

·      Have made Apache Spark or MapReduce style applications in the past

·      Knowledge of distributed data storage with Hadoop, Cassandra, or equivalent

·      Experience with data stream ingestion such as Kafka or Amazon Kinesis

·      Real-time data-stream analytics with Hive, Presto, or equivalent

 

TOOLS WE USE:

If you’ve ever contributed to an open-source project on GitHub, you’ll be right at home at SwipeSense.

·      Git/Github for version control and code review

·      Pivotal for agile project management and bug tracking

·      Slack for communication.

·      CircleCI for continuous integration and automated testing

·      SumoLogic for log analysis, alerting, and metrics

 

 

Please note: position is full-time, at our Chicago headquarters. Must be local or willing to relocate. SwipeSense offers competitive compensation, stock options and excellent medical and dental benefits.  M/F/D/V

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