About The Position

We’re looking for a Senior Data Engineer to support the design, development, and optimization of data solutions for a high-impact enterprise initiative. This role is ideal for someone with strong hands-on experience in data processing, transformation, and validation, who thrives in building reliable and well-structured datasets for analytics and business workflows. You will work closely with cross-functional teams to ensure data is accurate, standardized, and ready for downstream consumption, contributing to scalable and high-quality data pipelines.

Requirements

  • 4+ years of experience in Data Engineering or Data Analytics roles with strong engineering focus.
  • Strong hands-on experience with Snowflake (Must).
  • Strong hands-on experience with Python for data processing and transformation.
  • Strong experience with SQL and working with large-scale datasets.
  • Proven experience in data validation, data transformation, and normalization.
  • Experience building and maintaining ETL pipelines and handling data ingestion workflows.
  • Strong attention to detail with a focus on data quality and reliability.
  • Ability to work in cross-functional environments and communicate effectively with stakeholders.

Nice To Haves

  • Experience working with Salesforce data structures.
  • Familiarity with Tamarac or similar RIA platforms.
  • Experience with Compass or SharePoint integrations.
  • Experience with file handling and ingestion processes (e.g., CSV, JSON, batch files).

Responsibilities

  • Design, develop, and maintain data pipelines to ingest, transform, and normalize data from multiple sources.
  • Lead the design and implementation of data ingestion architectures in Snowflake, ensuring scalability and reliability.
  • Apply best practices in data validation to ensure accuracy, consistency, and reliability across datasets.
  • Perform data transformation and normalization to support analytics and reporting use cases.
  • Work with large datasets using SQL and Python to process and analyze data efficiently.
  • Ensure data quality by implementing validation rules, checks, and monitoring processes.
  • Collaborate with business and technical stakeholders to understand data requirements and translate them into scalable solutions.
  • Support ETL processes and file handling workflows for structured and semi-structured data.
  • Contribute to documentation and continuous improvement of data processes and standards.

Benefits

  • Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
  • Access to AI learning paths to stay up to date with the latest technologies.
  • Study plans, courses, and additional certifications tailored to your role.
  • Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
  • English lessons to support your professional communication.
  • Travel opportunities to attend industry conferences and meet clients.
  • Career development plans and mentorship programs to help shape your path.
  • Special day rewards to celebrate birthdays, work anniversays, and other personal milestones.
  • Company-provided equipment.
  • Flexible working options to help you strike the right balance.
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