Sr. Consultant, Analytics Engineer

Introduction At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk Your role and responsibilities We are looking for a Sr. Consultant, Analytics Engineering to join our growing team of experts. This position sits at the intersection of data engineering and analytics, focused on transforming raw, ingested data into trusted, well-modeled, and well-documented assets that power decision-making, BI, and downstream AI/ML use cases.The Sr. Consultant, Analytics Engineering will own the design and delivery of dimensional and analytical data models, semantic layers, testing and observability frameworks, and CI/CD for analytics workflows. You will partner closely with Data Engineers (who own ingestion and platform), BI Developers, Analysts, and client stakeholders to translate business requirements into durable, reusable, version-controlled data products. You will lead modeling decisions on customer engagements and mentor junior analytics engineers and analysts on dbt, modeling patterns, and analytics best practices.The right candidate is excited about software engineering rigor applied to analytics: modular SQL, automated testing, peer review, lineage, and treating data models as products with SLAs and consumers.As of April 2025, Hakkoda has been acquired by IBM and will be integrated in the IBM organization. Your recruitment process will be managed by IBM. IBM will be the hiring entity.This role can be performed from anywhere in the US. Required technical and professional expertise u2022 Bachelor's degree in engineering, computer science, analytics, statistics, or equivalent practical experience.u2022 5+ years in analytics engineering, data modeling, BI engineering, or closely related roles delivering production analytics on cloud data platforms.u2022 Expert-level SQL: complex window functions, CTEs, query optimization, and warehouse-specific tuning (Snowflake preferred; Databricks, BigQuery, or Redshift acceptable).u2022 Production experience building, owning, and operating dbt projects (dbt Core or dbt Cloud), including macros, packages, Jinja templating, incremental models, snapshots, and exposures.u2022 Strong command of dimensional modeling (Kimball star/snowflake schemas, slowly changing dimensions, conformed dimensions) and pragmatic application of OBT, normalized, and Data Vault patterns where appropriate.u2022 Demonstrated ability to translate ambiguous business requirements into a layered modeling architecture (staging, intermediate, marts, semantic) with clear ownership, naming conventions, and documentation.u2022 Experience defining and governing metrics in a semantic layer (dbt Semantic Layer / MetricFlow, LookML, Cube, or equivalent), including metric definitions, dimensional consistency, and downstream BI exposure.u2022 Hands-on experience implementing data quality and testing frameworks: dbt tests (generic and singular), data contracts, freshness checks, anomaly detection, and lineage-based impact analysis.u2022 Git-based workflows for analytics: feature branching, pull requests, peer review, and CI/CD pipelines (GitHub Actions, GitLab CI, Azure DevOps, or similar) for dbt projects.u2022 Working knowledge of orchestration patterns and tools used to schedule transformation workloads (dbt Cloud, Airflow, Dagster, Prefect, or platform-native schedulers).u2022 Python scripting for analytics tooling, automation, and lightweight transformations where dbt/SQL is not the right fit.u2022 Cloud experience on AWS (Azure, GCP are nice to have as well).u2022 Experience integrating modeled data with BI and consumption tools (Tableau, Power BI, Looker, Sigma, Hex, Mode) and partnering with BI developers on semantic alignment.u2022 Track record of leading modeling decisions on client engagements, including reviewing and approving model designs from other engineers.u2022 Mentorship of junior analytics engineers and analysts on modeling patterns, dbt best practices, code review standards, and analytics engineering rigor.u2022 Ability to prepare technical and business-facing artifacts (model design docs, lineage maps, metric catalogs, runbooks) and present to internal and customer stakeholders.u2022 Track record of sound problem-solving skills and an action-oriented mindset.u2022 Strong interpersonal skills including assertiveness and ability to build strong client relationships, particularly with analyst and business stakeholders.u2022 Ability to work in Agile teams.u2022 Experience hiring, developing, and managing a technical team. Preferred technical and professional experience u2022 Snowflake certifications (SnowPro Core, SnowPro Advanced: Data Engineer or Architect) or dbt certifications (dbt Analytics Engineer, dbt Cloud Developer).u2022 Experience with reverse-ETL tooling (Hightouch, Census) and operational analytics use cases.u2022 Experience designing and governing a semantic/metrics layer at scale, including metric versioning, deprecation, and stakeholder alignment across multiple consumers.u2022 Familiarity with data catalog and observability tooling (Atlan, Alation, Collibra, Monte Carlo, Elementary, Soda) and integrating these with dbt projects.u2022 Experience supporting AI/ML and feature-store use cases with curated, well-tested analytics datasets.u2022 Familiarity with data contracts, model SLAs, and treating analytics models as versioned, consumer-facing products.u2022 Industry experience in financial services, healthcare/life sciences, retail/CPG, or public sector.IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

Created: 2026-04-30