Data Engineer II - California, United States - Redica Systems, Inc.

Redica Systems, Inc. California, United States

3 weeks ago

Description

Redica Systems is a SaaS start-up serving more than 200 customers within the life science sector, with a specific focus on Pharmaceuticals and MedTech.

Embracing a hybrid model, our workforce is distributed globally, with headquarters in Pleasanton, CA.
Redica's data analytics platform empowers companies to improve product quality and navigate evolving regulations.

Using proprietary processes, we harness one of the industry's most comprehensive datasets, sourced from hundreds of health agencies and the Freedom of Information Act.

Our customers use Redica Systems to more effectively and efficiently manage their inspection preparation, monitor their supplier quality, and perform regulatory surveillance.

More information is available at
Job Description

We're looking for an experienced Data Engineer to join our team as we continue to develop the first-of-its-kind quality and regulatory intelligence (QRI) platform for the life science industry.

The ideal candidate will come with experience in designing, building, and maintaining data pipelines and infrastructure maintenance while remaining hands-on in the code.

Core Responsibilities
Develop infrastructure optimized for efficient extraction, transformation, and loading of data from diverse sources
Maintain a full understanding of our technical architecture along with its distinct subsystems
Proactively guide technical choices within your domain of expertise
Recommend and validate different ways to improve data reliability, efficiency, and quality
Apply Agile Scrum methodology, with a primary focus on delivering sustainable, high-performance, scalable, and easily maintainable enterprise solutions
Prioritize and address technical challenges, working closely with engineering managers
Identify optimal approaches for resolving data quality or consistency issues
Ensure successful system delivery to the production environment and assist the operations and support team in resolving production issues, as necessary
Design, test, and maintain data stores, databases, processing systems, and microservices
Collaborate with NLP/ML teams to integrate data pipeline with NLP/ML services
About you

Tech Savvy :
Effectively anticipates and adopts innovations in business-building technology solutions, staying up-to-date with data advancements and incorporating them into work processes

Manages Complexity :
Actively synthesizes solutions from complex information by identifying patterns and developing effective problem-solving strategies to solve data-related problems effectively

Decision Quality :
Consistently makes good and timely decisions that propel organizational progress and maintain data integrity

Collaborates :
Actively engages in collaborative problem-solving by leveraging diverse perspectives and finding innovative solutions to achieve shared goals and data engineering initiatives

Optimizes Work Processes :
Actively seeks opportunities to enhance and streamline current work processes for managing data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing

Drives Results :
Strives to continuously improve performance and exceed expectations to contribute to overall success and meet data-related deliverables

Strategic Mindset :
Consistently demonstrates a strategic mindset by envisioning future possibilities and successfully translating them into breakthrough data strategies, contributing to the organization's long-term success

Engaged:
Not only shares our values but also possesses the essential competencies needed to thrive at Redica
Qualifications

3+ years of experience with an emphasis on code/system architecture and quality output
Experience designing and building data pipelines, data APIs, and ETL/ELT processes
Exposure to data modeling and data warehouse concepts
Hands-on experience in Python
Hands-on experience working with AWS Sagemaker and supporting the building of batch and real-time ML pipelines (AWS Sagemaker / MLflow)
Hands-on experience setting up, configuring, and maintaining SQL and no-SQL databases (MySQL/MariaDB, PostgreSQL, MongoDB, Snowflake)
Computer Science, Computer Engineering, or similar technical degree
Bonus Points
Experience with the data engineering stack within AWS is a major plus (S3, Lake Formation, Lambda, Fargate, Kinesis Data Streams/Data Firehose, DynamoDB, Neptune DB)
Experience with event-driven data architectures
Experience with the ELK stack is a major plus (ElasticSearch, LogStash, Kibana)
Additional Information

All your information will be kept confidential according to EEO guidelines.

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