Our client is building a “born in the cloud” data platform to enable sales, finance, and marketing across our enterprise applications. We are seeking an experienced Data Engineer to solve our most difficult challenges as we expand our platform capabilities and increase in systems complexity.
- 12+ years of experience in a software or data engineering role
- 6+ years of experience in data modeling, data warehousing, and big data architectures
- 3+ years of above experience occurred within AWS (preferred), Azure, or Google Cloud
- Strong programming skills and ability to utilize a variety of software/languages/tools; e.g., Python (preferred), Skala, Java, Hive, SQL Analytical Function, SAS, PySpark, PL/SQL
- Strong experience with writing complex programs, implementing architectures, and enabling automation in these environments.
- Desirable: Experience in the following AWS Services: Data Migration Service (DMS), Glue, Elastic Map Reduce (EMR), Lambda, S3, Simple Notification Service (SNS), Step Functions, Redshift, Oracle RDS, Postgres SQL language, Glue Crawler, Athena, EC2, DynamoDB, Secrets Manager, Key Management Service, CloudTrail, CloudWatch, Simple Queue Service (SQS)
- Desirable: Experience working with various data source like Oracle, MySQL, ServiceNow, SFDC, EBS
- Desirable: Understanding of Amazon network and security essentials such as VPC, IAM, Subnets, Route 53, Policies
- Desirable: Understanding of Version Control and Deployment tools like GIT, Code Commit, Code Deploy, Code Pipeline
- Strong analytical and problem-solving skills
- Thrive on learning new technologies
- Provide hands-on technical leadership in data engineering design and implementations including the scaled application of data ingestion, data models, data structures, data storage, high-throughput data processing, data pipelines, machine learning, and platform monitoring (primarily in Python).
- Deliver work products built within and supported by microservice, API, event driven and serverless architectures, and built within enterprise security and networking policies (primarily in Python).
- Create and maintain Continuous Integration / Continuous Deployment (CI/CD) processes to deploy cloud-based analytics applications
- Develop and follow data engineering best practices with considerations for high data availability, computational efficiency, data latency, data security, cost, and quality.
- Within AWS, build and maintain environments, processes, functionalities, and tools to improve all stages of analytics solution development, e.g., proof of concepts and production.
- Leveraging AWS, develop frameworks which optimize the scalability, supportability, reliability, and cost of future Data Engineering solutions.
A Human Approach to Staffing
Our Company is committed to the principles of equal employment. We are committed to complying with all federal, state, and local laws providing equal employment opportunities, and all other employment laws and regulations. It is our intent to maintain a work environment which is free of harassment, discrimination, or retaliation because of sex, gender, race, religion, color, national origin, physical or mental disability, genetic information, marital status, age, sexual orientation, gender identity, military service, veteran status, or any other status protected by federal, state, or local laws. The Company is dedicated to the fulfillment of this policy in regard to all aspects of employment, including but not limited to recruiting, hiring, placement, transfer, training, promotion, rates of pay, and other compensation, termination, and all other terms, conditions, and privileges of employment.