- Optionales Büro in Noida
Main Duties:
- Rapidly gain fluency with the current-state data infrastructure and absorb the design and assessment materials produced by prior consulting work, translating them into actionable technical and sequencing plans.
- Proactively engage business stakeholders (Finance, Operational Leadership, FP&A) to understand high-priority business intelligence, reporting, and financial reconciliation needs.
- Define, model, and translate complex business requirements into concrete data pipelines and robust transformation logic within dbt, ensuring data quality, consistency, and fitness-for-purpose for Power BI consumption.
- Lead the architectural design and implementation of data modeling, transformation, and orchestration standards using dbt, Redshift, Estuary, and Power BI.
- Partner with the Data Engineering Leader to plan and sequence modernization workstreams and ensure technical execution aligns with architectural standards. Additional India-based engineering resources will be positioned for deployment to this initiative.
- Contribute directly to core dbt model and test development, ensuring speed, architectural quality, and maintainability.
- Collaborate with the Director of Data Quality & Governance to embed data quality, lineage, and governance frameworks into the platform’s design—including the enablement of automated data quality testing, proactive monitoring, and standardized issue resolution workflows.
- Explicitly design transformation logic to reconcile financial and operational data discrepancies and establish a Single Source of Truth for key metrics and metadata elements.
- Drive the migration and modernization of legacy workflows (Matillion, Power BI DAX) into version-controlled, tested, and documented dbt models.
- Establish and enforce best practices for Git-based workflows, CI/CD pipelines, and documentation across the data platform. Ensure the platform’s ongoing evolution remains structured, well-documented, and responsive to business analytical needs.
- Own the framework and standards for platform documentation, ensuring models, transformations, and dependencies are consistently described, discoverable, and integrated with governance processes. Leverage automation and AI-assisted tooling (e.g., dbt auto-docs, lineage visualization, metadata capture) to streamline and scale documentation, lineage tracking, and quality reporting.
- Mentor and upskill engineers and analysts supporting the initiative, embedding platform standards and reducing key-person risk.
- Architect the semantic model to maximize discoverability, optimize performance, reduce Power BI Premium capacity strain, and enable self-service analytics for business users.
- Develop and maintain metadata documentation that clearly defines dimensions and metrics in ways that are easy for other members of the data, operations, and business teams to understands.
Required:
- Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field strongly preferred; equivalent experience acceptable. Master’s degree or advanced certification in data science, data engineering or architecture is a plus.
- 7–10 years of progressive experience in data engineering, data architecture, or related technical disciplines, including at least 3 years leading or designing cloud-based data platform implementations (e.g., Redshift, Snowflake, BigQuery).
- Demonstrated success designing, implementing, and optimizing modern data stacks that include automated testing, documentation, and governance capabilities.
- Deep expertise in data modeling and transformation using dbt (or equivalent frameworks).
- Expert-level proficiency in SQL and data warehouse design principles.
- Proven ability to translate abstract business requirements into scalable, production-ready data models and dbt transformation logic.
- Strong proficiency in Python for automation, orchestration, and integration tasks related to data pipelines, testing, and CI/CD.
- Experience with real-time and batch ingestion tools such as Estuary, Fivetran, or Airbyte.
- Proficiency with Git-based development workflows, including branching, pull requests, and code reviews.
- Hands-on experience implementing CI/CD pipelines for data or analytics environments.
- Proven ability to lead complex technical initiatives and establish scalable engineering and documentation standards without formal managerial authority.
- Experience mentoring engineers and promoting consistent development best practices.
- Strong communication and collaboration skills, with the ability to engage both technical and business stakeholders.
- Familiarity with AWS data ecosystem (S3, Redshift, Glue, IAM) or comparable cloud platforms.
Preferred to have:
- Significant experience working directly with financial or operational reporting teams to define P&L, margin, and utilization metrics.
- Experience migrating legacy ETL or BI logic (e.g., Matillion, Power BI DAX) into code-based transformation frameworks such as dbt.
- Familiarity with Matillion, including its orchestration, transformation, and scheduling patterns, to support transition planning and migration.
- Experience with Power BI service administration, capacity management, and workspace governance.
- Exposure to data quality, lineage, and metadata management frameworks and experience with automation or AI-assisted documentation tools.
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