Job description

Job Description CapTech Data Engineering consultants enable clients to build and maintain advanced data systems that bring together data from disparate sources in order to enable decision-makers. We build pipelines and prepare data for use by data scientists, data analysts, and other data systems. We love solving problems and providing creative solutions for our clients. Cloud Data Engineers leverage the client’s cloud infrastructure to deliver this value today and to scale for the future. We enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other developers, architects, and our clients. Specific responsibilities for the Data Engineer – Cloud position include:  • Developing data pipelines and other data products using Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) • Advising clients on specific technologies and methodologies for utilizing cloud resources to efficiently ingest and process data quickly • Utilizing your skills in engineering best practices to solve complex data problems • Collaborating with end users, development staff, and business analysts to ensure that prospective data architecture plans maximize the value of client data across the organization.  • Articulating architectural differences between solution methods and the advantages/disadvantages of each Qualifications Typical experience for successful candidates includes:    • Experience delivering solutions on a major cloud platform • Ability to think strategically and relate architectural decisions/recommendations to business needs and client culture • Experience in the design and implementation of data architecture solutions • A wide range of production database experience, usually including substantial SQL expertise, database administration, and scripting data pipelines • Ability to assess and utilize traditional and modern architectural components required based on business needs.   • A demonstrable ability to deliver production data pipelines and other data products. This could be hands on experience, degree, certification, bootcamp, or other learning. Skills: Successful candidates usually have demonstrable experience with technologies in some of these categories: • Languages: SQL, Python, Java, R, C# / C++ / C • Database: SQL Server, PostgreSQL, Snowflake, Redshift, Aurora, Presto, BigQuery, Oracle • DevOps: git, docker, subversion, Kubernetes, Jenkins • Additional Technologies: Spark, Databricks, Kafka, Kinesis, Hadoop, Lambda, EMR • Popular Certifications: AWS Cloud Practitioner, Microsoft Azure Data Fundamentals, Google Associate Cloud Engineer

Requirements