Data Engineer

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Data Build Tool Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Data Engineer (Contract) Duration: 6 months (with potential to expand capacity) Engagement: Starting with 1 resource Role Overview We are seeking an experienced Data Engineer to build and maintain robust, scalable data pipelines on our cloud data platform. You will work within a modern Medallion architecture, delivering high-quality, well-tested data models and pipelines using dbt, Python, and modern orchestration tools. Key Responsibilities Design, build, and maintain dbt data models across Bronze, Silver, and Gold layers of a Medallion architecture Develop custom dbt macros to enforce modeling standards, reduce code duplication, and improve team productivity Write production-grade Python code for data ingestion, transformation, and processing workflows Build, schedule, and monitor data pipelines using orchestration platforms such as Dagster and Astronomer (Apache Airflow) Implement and manage CI/CD pipelines in GitLab for automated testing, linting, and deployment of dbt projects and Python packages Collaborate with data architects and analytics engineers to translate business requirements into clean, performant data models and pipelines Apply data modeling best practices including normalization, slowly changing dimensions, and star/snowflake schema design where appropriate Leverage AI-assisted development tools such as Amazon Q and Kiro to accelerate pipeline development Required Skills Expert-level proficiency in dbt (Core or Cloud), including advanced features such as custom macros, hooks, tests, and packages Strong Python development skills, including writing modular, testable, and maintainable code for data engineering use cases Experience building and managing orchestrated workflows using Dagster and/or Astronomer (Apache Airflow), including DAG authoring, sensors, and dependency management Strong experience with CI/CD pipelines using GitLab, including .gitlab-ci.yml authoring and pipeline optimization Solid understanding of data modeling principles and experience implementing Medallion (Bronze/Silver/Gold) architecture Proficiency in SQL and experience working with cloud data warehouses (Snowflake preferred) Exposure to AWS data services (S3, Glue, Lambda) in a data pipeline context Familiarity with data quality frameworks such as Great Expectations or dbt tests Familiarity with AI-assisted development tools (Amazon Q, Kiro, or similar) Nice to Have (will be mandatory skill set for future adds) Experience with PySpark for distributed data processing at scale 15 years full time education Important Notice We have been alerted to the existence of fraudulent messages asking job seekers to set up payment to cover various costs associated with establishing employment at Accenture. No one is ever required to pay for employment at Accenture. If you are contacted by someone asking for payment, please do not respond, and contact us at india.fc.check@accenture.com immediately. Equal Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.