Data Engineer

Stott and May are working with a digital client looking to bring on an experienced Data Engineer to support data platform build and optimization work across Snowflake and Databricks in AWS. You will join an existing agile team (of 6 existing members) as a senior engineer, with the need to add up to three engineers. This role suits someone who is hands on, comfortable working in modern cloud data stacks, and experienced in delivering production grade data pipelines in real world environments. This is a six month initial contract with a strong view to extend in six month increments. Rates are competitive, paying between $70–100 per hour depending on experience, at 40 hours per week. We engage contractors via W2 or personal LLC only and cannot work with C2C third parties. This position is FULLY REMOTE, working EST time zone. What you will be doing Building and maintaining data pipelines using Snowflake and Databricks Designing ELT workflows for analytics and downstream consumption Working with structured and semi structured data at scale Collaborating with analytics, data science, and platform teams Supporting performance, reliability, and cost optimization initiatives What we are looking for Strong experience as a Data Engineer in cloud environments Hands on Snowflake experience in production Hands on Databricks experience using Spark or PySpark AWS experience across core services used in data platforms Strong SQL skills and solid Python experience Experience working in agile, delivery focused teams Nice to have dbt or analytics engineering exposure Streaming or near real time data experience Experience supporting data science or ML workloads Why this role Modern data stack Meaningful engineering work, not just maintenance Flexible engagement model, extensions likely Opportunity to work with experienced data teams