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Analytical Engineer

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Onsite

Analytical Engineer

Big Oh Tech

Analytical Engineer

Skills

SQL QueriesBig DataTableauSnowflakeGitBitbucketData AnalysisMetabasedbtOracleApache AirflowSupply Chain ManagementPower BI

1 month ago

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Important information


Contract type:

Permanent

Location:

Noida, Uttar Pradesh, India

Work mode:

Onsite

Published on:

14 September 2026

What they need


About Company:

Big Oh Notation Pvt. Ltd. are an ISO 27001 & CMMI Level 3 certified IT product and services company specializing in AI-led digital transformation and enterprise software engineering. We are the technology partner for AI-driven products, including Digilawyer, Costimizer.ai, and Botshot.ai, delivering scalable solutions across intelligent automation and applied AI systems.

Bigohtech.com

We are seeking an experienced Analytics Engineer to design, develop, and maintain enterprise-scale analytics data products and reporting solutions. The role involves building scalable data transformation pipelines using DBT, implementing dimensional datamodels, enabling self-service analytics, and partnering with business stakeholders across Supply Chain, Finance, Sales, Customer, andOperations domains.

The candidate should possess strong expertise in SQL, DBT, data warehousing, performance optimization, and analytics engineering best practices, while driving high-quality, production-grade data assets.

Technical Skills

  • Strong experience in DBT (Data Build Tool).
  • Expert SQL development skills.
  • Experience with Spark SQL / Trino / Presto.
  • Strong understanding of Data Warehousing concepts.
  • Experience in Dimensional Modelling (Star/Snowflake Schema).
  • Airflow workflow orchestration.
  • Git/Bitbucket version control.
  • Performance tuning and query optimization.
  • Big Data architecture and implementation.
  • Data Quality and Reconciliation frameworks.

Database Technologies

  • Oracle
  • Hive
  • Spark

BI & Visualization

Hands-on experience with:

  • Metabase
  • Tableau

Key Responsibilities

Analytics Engineering & Data Transformation

  • Design, develop and maintain scalable DBT models and data pipelines.
  • Implement Medallion/Data Mesh architecture principles.
  • Develop incremental and full-load transformation frameworks using DBT.
  • Build reusable macros, tests, snapshots, and documentation.
  • Ensure data quality through automated validation and reconciliation checks.
  • Optimize DBT models for performance, scalability, and cost efficiency.

Data Modeling

  • Create Enterprise Data Models, Dimensional Models, Star Schemas, and Fact-Dimension structures.
  • Design subject-area marts for Finance, SCM, Customer, Sales, and Operations.
  • Define KPI calculations, business metrics, and semantic layer standards.
  • Collaborate with business teams to convert requirements into analytical data products.

Reporting & Analytics Enablement

  • Support reporting platforms such as Metabase, Power BI, Tableau, or equivalent BI tools.
  • Build curated datasets for dashboards and self-service analytics.
  • Develop reconciliation and operational monitoring reports.
  • Enable conversational analytics and KPI-driven reporting frameworks.

Engineering & DevOps

  • Work with Airflow orchestration and scheduling frameworks.
  • Implement CI/CD practices for DBT deployments.
  • Conduct code reviews and establish coding standards.
  • Monitor production jobs and troubleshoot performance bottlenecks.
  • Participate in release planning, deployment, and production support activities.

Stakeholder Management

  • Engage with business users and functional teams to understand requirements.
  • Drive requirement workshops and solution discussions.
  • Prepare technical documentation, HLDs, source-to-target mappings, and data lineage documents.
  • Mentor junior developers and analysts

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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