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Position: Data Engineer (Snowflake, DBT/ Matillion), Ahmedabad / Hyderabad Department: Information Technology | Role: Full-time | Experience: 3 to 5 Years | Number of Positions: 2 | Location: Ahmedabad / Hyderabad Skillset Snowflake, DBT/Matillion, Azure Cloud, Data Factory, Data Bricks, Data Warehousing, SQL, ETL/ELT, SSIS, Cloud Storage, Excellent English communication skills Job Description About Us We provide companies with innovative technology solutions for everyday business problems. Our passion is to help clients become intelligent, information-driven organizations, where fact-based decision-making is embedded into daily operations, which leads to better processes and outcomes. Our team combines strategic consulting services with growth-enabling technologies to evaluate risk, manage data, and leverage AI and automated processes more effectively. With deep, big four consulting experience in business transformation and efficient processes, we are a game-changer in any operations strategy. We are looking for an experienced and results-driven Data Engineer to join our growing Data Engineering team. The ideal candidate will be proficient in building scalable, high-performance data transformation pipelines using Snowflake and DBT or Matillion and be able to effectively work in a consulting setup. In this role, you will be instrumental in ingesting, transforming, and delivering high-quality data to enable data-driven decision-making across the clients organization. Key Responsibilities: Design and implement scalable ELT pipelines using dbt on Snowflake, following industry accepted best practices.Build ingestion pipelines from various sources including relational databases, APIs, cloud storage and flat files into Snowflake.Implement data modelling and transformation logic to support layered architecture (e.g., staging, intermediate, and mart layers or medallion architecture) to enable reliable and reusable data assets.Leverage orchestration tools (e.g., Airflow,dbt Cloud, or Azure Data Factory) to schedule and monitor data workflows.Apply dbt best practices: modular SQL development, testing, documentation, and version control.Perform performance optimizations in dbt/Snowflake through clustering, query profiling, materialization, partitioning, and efficient SQL design.Apply CI/CD and Git-based workflows for version-controlled deployments.Contribute to growing internal knowledge base of dbt macros, conventions, and testing frameworks.Collaborate with multiple stakeholders such as data analysts, data scientists, and data architects to understand requirements and deliver clean, validated datasets.Write well-documented, maintainable code using Git for version control and CI/CD processes.Participate in Agile ceremonies including sprint planning, stand-ups, and retrospectives.Support consulting engagements through clear documentation, demos, and delivery of client-ready solutions.Required Qualifications: 3 to 5 years of experience in data engineering roles, with 2+ years of hands-on experience in Snowflake and DBT or Matillion (Matillion-DPC is highly preferred, not mandatory Experience building and deploying DBT models in a production environment. Expert-level SQL and strong understanding of ELT principles. Strong understanding of ELT patterns and data modelling (Kimball/Dimensional preferred). Familiarity with data quality and validation techniques: dbt tests, dbt docs etc. Experience with Git, CI/CD, and deployment workflows in a team setting Familiarity with orchestrating workflows using tools like dbt Cloud, Airflow, or Azure Data Factory. Core Competencies: o Data Engineering and ELT Development: Building robust and modular data pipelines using dbt.Writing efficient SQL for data transformation and performance tuning in Snowflake.Managing environments, sources, and deployment pipelines in dbt. o Cloud Data Platform Expertise: Strong proficiency with Snowflake: warehouse sizing, query profiling, data loading, and performance optimization. Experience working with cloud storage (Azure Data Lake, AWS S3, or GCS) for ingestion and external stages. Technical Toolset: o Languages & Frameworks: Python: For data transformation, notebook development, automation. SQL: Strong grasp of SQL for querying and performance tuning. Best Practices and Standa .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.