Data Analytics Engineer: SQL, dbt & Dashboards

Tata Consultancy Services; New York (NY); On-site; USD 120,000 - 130,000; Full time

Job summary

Tata Consultancy Services in New York seeks an Analytics Engineer to design and maintain data transformations and models, using dbt and SQL to support analytical needs. You will build robust data pipelines and help ensure data quality across the data platform.

Develop reports and dashboards to surface insights, and collaborate with analytics and engineering teams to translate business requirements into scalable data solutions.

Qualifications

• 1–3 years of experience in analytics engineering, data engineering, or a related field.
• Proficiency in SQL; experience with dbt or similar transformation tools.
• Familiarity with data warehousing concepts and analytics best practices.
• Strong attention to detail and commitment to data quality.
• Ability to work collaboratively in a fast-paced, team-oriented environment.

Responsibilities

• Contribute to the development of data transformation logic and maintain existing data models using dbt and SQL.
• Write and optimize SQL queries for data transformation and analysis.
• Assist in implementing and maintaining data quality checks and testing procedures.
• Contribute to documentation of data models, transformations, and business logic.
• Develop and maintain reports and dashboards using visualization tools to surface actionable insights.
• Support the delivery of business and operational metrics in partnership with Analytics and senior team members.
• Work jointly with team members and stakeholders to accomplish shared outcomes and translate business requirements into data needs.

Skills

SQL

dbt

Data warehousing concepts

Data quality

Collaboration

Education

Bachelor of Computer Science

Tools

dbt

Looker

Tableau

Job description

Tata Consultancy Services in New York seeks an Analytics Engineer to design and maintain data transformations and models, using dbt and SQL to support analytical needs. You will build robust data pipelines and help ensure data quality across the data platform.

Develop reports and dashboards to surface insights, and collaborate with analytics and engineering teams to translate business requirements into scalable data solutions.