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If you are a Junior, Mid-Level, and Senior Data Engineers/Developers looking for excitement, challenge and stability in your work, then you would be glad to come across this page.
We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long term project. Here are a few details.
Check if you are up for maximizing your earning/growth potential, leveraging our Disruptive Talent Solution.
Location:NYC,NY OR Boston,MA
Exp: 3-10+ Years
We are seeking Junior Data Engineers/Developers with hands-on experience in AWS and Snowflake to support the migration of enterprise data infrastructure from SQL Server to AWS/Snowflake . This is an exciting opportunity for candidates who are passionate about cloud data platforms, modern data architecture, and want to be part of a digital transformation journey.
Assist in migrating data pipelines and datasets from on-premises SQL Server to Snowflake on AWS .
Build and maintain ETL/ELT pipelines using AWS native services (Glue, Lambda, S3, etc.).
Perform data transformation, cleansing, and validation for reporting and analytics use cases.
Work closely with senior data engineers and architects to follow best practices and standards.
Support development and testing activities including performance tuning, validation, and issue resolution.
Participate in unit testing, data validation, and documentation of data flow processes.
Collaborate with business analysts and data scientists to ensure data availability and accuracy.
Monitor data pipeline performance and assist in troubleshooting any data issues.
1–3 years of experience as a Data Engineer or Developer.
Good understanding of SQL Server schema design, stored procedures, and T-SQL queries.
Experience with Snowflake , including writing SQL scripts, working with Snowpipe, and understanding of virtual warehouses and roles.
Hands-on knowledge of AWS services like S3, Lambda, Glue, IAM, and CloudWatch.
Familiarity with data migration strategies and working with large datasets.
Basic understanding of data warehousing concepts and data modeling (star/snowflake schema) .
Strong SQL skills for querying, transforming, and validating data.
Familiarity with Python or any scripting language for data pipeline automation is a plus.
Exposure to tools like dbt , Airflow, or Talend is desirable.
AWS Certified (e.g., AWS Certified Data Analytics – Specialty or AWS Certified Developer – Associate) is a plus.
Experience working in an Agile environment .
Exposure to CI/CD pipelines and version control systems (e.g., Git).
Strong communication and interpersonal skills.
Ability to work both independently and collaboratively in a fast-paced environment.
Detail-oriented with strong problem-solving and analytical skills.
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