Data Engineer

We're looking for a Data Engineer. Headquartered in Los Angeles, California, Right Balance provides top-tier technology talent for innovative companies in the US. We’re in the top 50 companies to watch in LA. Our client is a global technology consultancy focused on designing and implementing secure, observable cloud architectures embracing an Everything as Code (EAC) approach so our clients can focus on their business goals. We can provide strategy, design, implementation, and follow-the-sun support. They also create custom software products when there are missing links in current solutions. Role We are seeking a skilled AWS Data Engineer to join our team and help shape the future of data management and analytics for our organization. In this role, you will work with a variety of AWS services to design, build, and optimize data pipelines, enabling data-driven decision-making at scale. Other Details: Location: Reston, VA. Local candidates are preferable. Length: 2+ years, long term. Open to W2 full-time with benefits or C2C. Learn and evolve your skills using the latest technology tools in a rapidly growing company. Learn from the best people around you. We constantly challenge the status quo and invent new ways of building a great product. Work on challenging problems, innovate, and positively impact many people's lives while having fun doing it. Minimum Requirements: Upper-intermediate to fluent speaking and writing English. Able to have a real-time conversation. 4+ years of full-time hands-on Data Engineer experience. 4+ years of full-time hands-on SQL experience. 4+ years of full-time hands-on AWS experience. 3+ years of full-time hands-on Redshift/EMR/Glue experience. 3+ years of full-time hands-on Data modeling/Snowflake experience. 3+ years of full-time hands-on Python experience. 3+ years of full-time hands-on PySpark experience. Strong expertise in SQL and experience with Redshift stored procedures. Proficiency with AWS services, including S3, Lambda, DynamoDB, Step Functions, RDS, SNS, and SQS. Experience with data engineering tools such as EMR, Glue, and Redshift. Strong knowledge of databases, including PostgreSQL and Aurora. Experience with data modeling techniques, including Star/Snowflake Schema Design. Proficiency in Python and PySpark for data manipulation and processing. Knowledge of serverless architectures and experience with AWS Lambda and Step Functions. Strong SQL and PL/SQL skills for querying and managing data. Familiarity with data warehousing concepts, including Datamarts and Multi-Dimensional OLAP. Familiarity with data processing frameworks such as Apache Spark or Hadoop. Knowledge of programming languages such as Python or Java for data manipulation and automation. Strong understanding of data governance and best practices for data quality. Experience working in Agile development environments. Excellent problem-solving skills and attention to detail. Strong verbal and written communication skills, with the ability to present information clearly to stakeholders. Knowledge of SAS, familiarity with DevOps tools (e.g., Jenkins, Bitbucket, GitLab, Terraform), experience with testing automation. Bachelor’s degree in Computer Science or equivalent demonstrated ability. The majority of our clients are venture-backed startups at the growth stage. Usually, at this stage, the company has already achieved product-market fit and is looking to expand rapidly. That’s where we bring the best engineering practices, strong architecture, the latest technologies, and consistent processes to help companies scale.

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