Data Engineer (AWS, Azure, GCP)

Requirements

• 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
• Learning & Development - Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
• Modern Health -A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life's ups and downs
• Carrot Fertility -Inclusive fertility and family-forming coverage for all paths to parenthood - including adoption, surrogacy, fertility treatments, pregnancy, and more - and opportunities for employer-sponsored funds to help pay for care
• Fringe -A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them - ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
• Employee Resource Groups - Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
• Philanthropic Partnerships - Opportunities to engage in partnerships and pro-bono projects that support our communities.
• 401(k) Matching - Generous matching and no vesting period to help you continue to build financial wellness

Benefits

Additional Information

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 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.

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