(IND) Information Systems Engineer 3

Description:

Important Points to consider:

• No sub contracting. Candidate must be on your direct payroll from Day-1.
• Prefer Candidates worked for well known and reputed companies(this Eliminates fake profiles)
• Prioritise Local profiles first and then go with non-locals (3:2 ratio- 3 locals, 2 non-locals - it will be easy for locals to be converted in future).
• Get candidates within the rates given.
• Find candidates with Minimum 7+ years of experience.
• Screen them twice if possible on video before submitting- Technical screening.
• Resume format:
  • Resume must be the full original resume that contains all past project (Project start/end dates, Project company/client names and locations for the project).
    
  • No single page profile and cover letters
  • Top of resume: Worker full Name, linked ID, current location and availability to join

  • Certifications are clearly mentioned (if required as per requirement)

  • Whole resume to be in Single format and font

  • Check alignment

  • No vendor Name/Logo on the resume

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Actual Title of the role: Snowflake Data Warehouse Engineer

Duration: 6-12 months

Max BR: BR/hr.

Onsite/Hybrid/Remote: Remote

Only Locals/Nonlocals can be submitted: Any (Locals Preferred)

Mode of interview: Zoom Video

No of rounds of interview: 2

Top Skills:

• Snowflake Data Warehousing

• SQL

• Data Modeling

• Transformations

• Stored Procedures

• Data Reconciliation

• Debug pipelines

Detailed Job description: Senior Snowflake Data Warehouse Engineer

Position Summary

• We are seeking an experienced Senior Snowflake Data Warehouse Engineer Consultant with deep expertise in enterprise data warehousing, dimensional modeling, analytical data structures, and Snowflake development. This is not primarily a data integration or data movement role. The position is focused on designing and developing robust, scalable, business-aligned data warehouse solutions that support enterprise reporting, analytics, semantic layers, and downstream data products.

• The ideal candidate will have strong hands-on experience building enterprise data warehouse solutions using Snowflake, advanced SQL, dimensional modeling, Python, and orchestration frameworks such as Airflow. The candidate should be comfortable translating complex business requirements into well-designed fact tables, dimensions, curated data models, and reusable analytical datasets.

• The consultant will be expected to independently execute complex development work while operating within established enterprise architecture, engineering, security, and governance standards.

Key Responsibilities

• Design and develop scalable enterprise data warehouse solutions on Snowflake.

• Build and maintain dimensional data models, including fact tables, dimension tables, conformed dimensions, aggregates, and curated analytical datasets.

• Translate business processes and analytical requirements into well-structured logical and physical data models.

• Work with business and analytics teams to understand KPIs, measures, dimensions, hierarchies, and reporting requirements.

• Develop complex SQL transformations and business logic supporting enterprise reporting and analytics.

• Design and implement ELT pipelines using Snowflake, SQL, Python, and Airflow.

• Perform source-system analysis, data profiling, source-to-target mapping, transformation design, and data reconciliation.

• Ensure data models are reusable, performant, understandable, and aligned with established enterprise data standards.

• Implement data-quality controls, reconciliation rules, and validation frameworks across warehouse layers.

• Troubleshoot complex data issues involving business logic, data lineage, transformations, and downstream reporting.

• Optimize Snowflake queries, data models, warehouse utilization, and overall workload performance.

• Develop and maintain Snowflake objects including tables, views, secure views, streams, tasks, dynamic tables, stored procedures, and functions.

• Participate in peer reviews for SQL, data models, and technical designs.

• Develop production-quality solutions that adhere to established coding, testing, documentation, and deployment standards.

• Use Git-based development workflows, merge/pull requests, and CI/CD practices to manage and deploy changes across environments.

• Support production deployments, incident resolution, troubleshooting, and root-cause analysis.

• Collaborate effectively with distributed engineering teams, analysts, architects, and business stakeholders.

Required Qualifications

• 7+ years of hands-on experience in data warehousing, business intelligence engineering, analytics engineering, or enterprise data platform development.

• 5+ years of experience designing and developing enterprise data warehouse solutions, including dimensional and analytical data models.

• Strong hands-on experience with Snowflake in a production enterprise environment.

• Advanced SQL expertise, including complex transformations, analytical functions, CTEs, performance tuning, and large-scale data processing.

• Strong understanding of dimensional modeling concepts, including fact and dimension tables, star and snowflake schemas, slowly changing dimensions, conformed dimensions, surrogate keys, grain definition, additive and semi-additive measures, and historical data management.

• Experience translating business requirements into logical and physical data models.

• Strong understanding of enterprise data warehouse architecture, ETL/ELT patterns, and curated analytical layers.

• Experience developing pipelines using Python and orchestration tools such as Apache Airflow.

• Experience with data profiling, source-to-target mapping, reconciliation, and data-quality validation.

• Experience with Git-based development, code reviews, and CI/CD practices.

• Strong troubleshooting and problem-solving skills across data models, transformations, pipelines, and reporting outputs.

• Ability to independently execute complex data warehouse development from requirements through production deployment.

• Strong written and verbal communication skills and the ability to work effectively with both technical and business stakeholders.

Preferred Qualifications

• Experience with dbt or similar SQL-based transformation and modeling frameworks.

• Experience with Snowflake capabilities such as Streams, Tasks, Dynamic Tables, Snowpipe, Snowpark, cloning, secure views, and data sharing.

• Experience with layered data architectures such as Bronze / Silver / Gold or equivalent enterprise warehouse patterns.

• Experience integrating enterprise data from systems such as SAP, Workday, Salesforce, Oracle, or other ERP/HCM/CRM platforms.

• Experience supporting analytical platforms such as Tableau, ThoughtSpot, or Power BI.

• Familiarity with semantic modeling, metadata management, data lineage, governance, and data-quality frameworks.

• Hands-on experience with Snowflake Cortex AI capabilities, including one or more of the following:

• Cortex Analyst and Semantic Views

• Cortex Agents

• Cortex AI Functions

• Cortex Search

• Large language model functions and prompt-based data processing within Snowflake

• Building AI-enabled analytical or data-management solutions using governed enterprise data

• Understanding of how semantic models, governed data assets, and AI agents can be combined to deliver reliable enterprise AI use cases.

• Exposure to retrieval-augmented generation, vector search, or agentic workflows within the Snowflake ecosystem is a plus.

No

Job Posting Type

Additional Details

• Pre-identified worker (First Name, Last Name) & Supplier Name : (No Value)
• Job Posting Type : Agency Recruited Worker Required
• Shift : Regular Shift
• Worker Legal Name (For Manager Sourced Only) : (No Value)