Consulting Partner - Data & Analytics

Role: Consulting Partner

Required Skills: Artificial Intelligence

Qualification: BACHELOR OF COMPUTER SCIENCE

Experience: 12 - 25 Years

Function: TECHNOLOGY

Apply By: 2026-12-25

Role: Consulting Partner - Data & Analytics

Location: Santa Clara, CA

We are seeking a consulting partner to be the on-the-ground face of the Data & Analytics unit serving

high-tech customers on the US West Coast. This is a broad, hands-on, customer-facing role spanning

advisory, solutioning, asset building and program execution - suited to someone who enjoys operating

across the full breadth of the data agenda rather than a single specialism.

Key Responsibilities

• Customer engagement and advisory: Build and sustain trusted relationships with client data

engineering, platform, architecture and analytics teams. Travel to customer sites across the US West

Coast to run discovery conversations, executive briefings and capability sessions.

• Solution workshops: Plan and facilitate solution and design workshops - frame the problem, shape

options, whiteboard target architectures and convert outcomes into actionable proposals.

• Solutioning and proposals: Own or contribute to RFP, RFI and proactive proposal responses - solution

approach, architecture, estimation, delivery model and pricing inputs - and present and defend them to

technical and business audiences.

• Asset and offering planning: Identify reusable asset opportunities from live customer demand; define

accelerators, PoVs, demos and reference architectures, and drive them to completion with the CoE pods.

• Representing the Centres of Excellence: Act as the customer-facing voice of the Data and AI CoEs - bring

the right pod, offering and expertise into the account, and carry customer insight back to shape the CoE

roadmap.

• Program planning and execution: Work with offshore delivery and CoE teams on program planning,

estimation, staffing and execution governance for key programs; guide design decisions, review

deliverables and safeguard quality and outcomes.

• Technology currency and capability building: Maintain an informed point of view on modern data

architecture, open-source engineering and AI trends relevant to high-tech customers; contribute to

skilling priorities and mentor engineers and consultants.

• Pipeline contribution: Identify and qualify opportunities within accounts, maintain a credible view of

technical pipeline and work with account leadership to convert.

Qualifications

Education: Bachelor's degree in Computer Science, Engineering or related discipline; Master's preferred.

Must-Have Technical / Functional Skills

Data & Analytics platform engineering - core of the role

• Modern warehousing, lakehouse and open data architecture: semantic data modelling, medallion

architecture, Apache Iceberg / Delta, Trino / Presto, dbt, and Data Mesh / data product design for

reusable, governed datasets.

• Cloud data and analytics platforms - deep expertise in at least one, credible familiarity with a second:

Google Cloud (BigQuery, Dataflow, Dataproc, Pub/Sub, Dataplex, Looker, Vertex AI), Azure (Synapse,

Fabric, ADF, Purview, Azure ML) or AWS (Redshift, Glue, EMR, Kinesis, SageMaker); Databricks and/or

Snowflake, including workload design and query performance tuning.

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Publication-ready job description

• Deep, hands-on data engineering at scale: enterprise data pipelines using Apache Spark / PySpark,

advanced SQL and Python; batch and streaming ingestion with Kafka and/or Flink; orchestration and

SLA-driven operations with Airflow.

• Analytics and consumption enablement: the semantic and reporting layer that turns data products into

decisions - Looker / LookML, Power BI or Tableau - with self-service enablement and analytics engineering

practices.

• DataOps and platform reliability: CI/CD for data pipelines (GitHub Actions / Azure DevOps), Terraform,

Kubernetes, data observability and lineage, and FinOps for cost and performance optimisation of large

data platforms.

Data governance, AI and analytics breadth

• Data governance, quality, lineage, metadata, MDM and privacy engineering; catalog tooling such as

Dataplex, Collibra, Alation, Purview or Unity Catalog.

• AI & GenAI led Transformation experience.
• Working knowledge of the AI stack - ML and MLOps (MLflow, Kubeflow, Ray, feature stores), GenAI and

agentic patterns (RAG, vector stores, LLM evaluation and guardrails) and Responsible AI practices.

Consulting, solutioning and engagement skills

• Proven experience in a customer-facing role - running discovery and solution workshops, presenting to

senior engineering and business stakeholders, and building trusted technical relationships.

• Demonstrated ownership of RFP / RFI and proactive proposal responses: solution approach, architecture,

estimation, delivery model and orals.

• Experience building reusable assets - Accelerators, PoVs, PoCs, demos and reference architectures - and

representing a practice or Centre of Excellence.

• Experience in planning and governing programs executed with distributed onsite-offshore teams.

Domain context

• Experience with high-technology customers - hyperscalers, platform, software, semiconductor,

consumer-electronics and comfort working alongside engineering-led organisations that build much of

their own stack.

Generic Managerial Skills

• Strong consultative and communication skills - credible with principal engineers and confident

presenting to executive stakeholders.

• Willingness and ability to travel regularly to customer locations across the US West Coast.
• Experience coordinating across geographies and time zones with offshore delivery and CoE teams;

mentoring without direct line management.

• Comfortable working in evolving environments - self-directed, pragmatic and able to build structure

where needed

Salary Range: $160,700 - $220,000

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