Technical Delivery Consultant (Data & Analytics)

Job Title: Technical Delivery Consultant (Data & Analytics) Experience Level: 4–7 Years Location: Islamabad About the Role We are looking for a proactive Technical Delivery Consultant to join our Data & Analytics consulting practice.

In this role, you will not only lead the technical execution of data platform implementations but also act as a quality gatekeeper—reviewing ongoing projects and guiding teams toward the right architectural decisions.

Additionally, you will partner with our sales and client success teams to engage with prospective customers, understand their challenges, and propose fit-for-purpose data solutions.

This role demands a rare mix of hands-on technical depth, delivery discipline, and consultative communication skills.

Key Responsibilities 1.

Delivery Leadership (Project Execution) Lead end-to-end technical delivery of data platform implementation projects (e.g., data warehousing, data lakes, lakehouses, or modern BI platforms).

Translate business requirements into technical specifications, architecture blueprints, and development tasks.

Manage technical risks and dependencies; ensure projects are delivered on time, within scope, and with high quality.

Collaborate with junior developers, data engineers, and cross-functional teams to drive execution.

• 2.

Technical Governance & Quality Assurance Perform periodic technical health checks on in-progress projects to validate the technical approach, code quality, and architectural decisions.

Identify areas of technical debt, performance bottlenecks, or scalability concerns and recommend actionable improvements.

Establish and enforce best practices for data modeling, ETL/ELT pipelines, data governance, and security.

Conduct peer reviews and technical audits to ensure consistency across multiple client engagements.

• 3.

Pre-Sales & Solutioning Support Participate in technical discovery meetings with prospect customers to understand their data challenges, existing landscape, and success criteria.

Design and present high-level solution architectures, technology recommendations, and effort estimates.

Articulate the value proposition of proposed solutions clearly to both technical and non-technical stakeholders.

Build proof-of-concepts (PoCs) or reference architectures to demonstrate technical feasibility during sales cycles.

• 4.

Client & Stakeholder Communication Serve as a trusted technical advisor to client technical leads and architects.

Facilitate workshops, sprint reviews, and technical status updates with clarity and confidence.

Translate complex technical concepts (e.g., partitioning strategies, incremental loads, data lineage) into business-friendly language.

Required Qualifications Technical Expertise: 4–7 years of hands-on experience in data platform implementation (cloud or on-prem).

Strong proficiency in SQL and at least one programming language (Python, Scala, or Java).

Experience with cloud data platforms (Snowflake, BigQuery, Redshift, Synapse, or Databricks).

Solid understanding of data modeling (Kimball, Inmon, Data Vault), ETL/ELT patterns, and workflow orchestration (Airflow, dbt, Azure Data Factory, or similar).

Familiarity with data governance, cataloging, and quality tools (Collibra, Purview, Great Expectations, etc.) is a plus.

Delivery & Process Skills: Proven experience leading technical workstreams within Agile/Scrum or hybrid methodologies.

Experience conducting technical reviews, audits, or readiness assessments on live projects.

Ability to balance speed of delivery with long-term maintainability and performance.

Consulting & Communication: Excellent verbal and written communication skills – able to lead technical conversations with customers and internal stakeholders.

Comfortable creating solution architecture diagrams, slide decks, and proposals for prospect meetings.

Prior experience supporting pre-sales (estimations, solutioning, PoCs) is highly desirable.

Strong problem-solving mindset with the ability to push back constructively when needed.

Nice to Have Cloud certification (AWS Solutions Architect, Azure Data Engineer, or GCP Data Engineer).

Experience with modern data stack (dbt, Airbyte, Fivetran, Looker, Power BI).

Background working in a consulting or services organization (client-facing delivery).

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