Senior Data Engineer

Company Description

As a technology consulting and delivery company, DAIC partners with businesses to unlock the power of their data, optimize their technology infrastructure, and drive data-driven success. We provide expert guidance and solutions in data analytics and cloud technologies. Our mission is to empower businesses to transform data into actionable insights, leverage the cloud for agility and scalability, and ultimately thrive in the digital age.

Role Description

• Lead the end-to-end migration

  of data warehousing and ETL processes from

  Teradata

  and

  Informatica

  to

  Snowflake

  and

  dbt

  .
• Design, develop, and implement highly efficient, scalable, and reliable

  ETL/ELT pipelines

  within the new Snowflake and dbt environment.
• Optimize existing Teradata SQL and Informatica workflows for performance and cost-efficiency on the Snowflake platform.
• Establish and enforce

  data quality, governance, and security standards

  within the new platform.
• Collaborate with data architects, analysts, and business stakeholders to understand data requirements and translate them into robust technical solutions.
• Develop

  best practices

  for data modeling, CI/CD, and version control (using Git) for the new data platform.
• Mentor junior engineers and contribute to the continuous improvement of the data engineering practice.
• Troubleshoot and resolve complex data integration and data warehouse performance issues.

Qualifications

• 5–10 years

  of professional experience in data engineering, data warehousing, or a related field.

• Deep, demonstrable expertise

  in migrating data platforms from on-premises/legacy systems to cloud environments (preferably AWS, Azure, or GCP).

• Mandatory hands-on experience

  with

  Teradata

  for data warehousing and

  Informatica

  for ETL development.

• Expert-level proficiency

  in

  Snowflake

  data warehousing, including performance tuning, SnowSQL, and platform administration.
• Strong experience with

  dbt (data build tool)

  for data transformation, testing, and documentation.
• Exceptional proficiency in

  SQL

  and at least one programming language (Python is strongly preferred).
• Experience with

  cloud services

  (e.g., S3, ADLS, Google Cloud Storage) and setting up data ingestion from various sources.
• Excellent analytical, problem-solving, and communication skills.