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THE ROLE

As Head of Data Practice & Delivery, you will be the technical and delivery anchor of our data capability. This role is execution-centric you will own the architecture, delivery, and commercial success of complex enterprise data programs, embedding modern data engineering practices across accounts while growing a high-performance team. You will translate data strategy into measurable outcomes: reliable pipelines, governed platforms, and trusted data products that drive real business value.

KEY RESPONSIBILITIES:

Data Platform Delivery & Cloud-Native Engineering

•Own end-to-end delivery of enterprise data transformation programs on AWS, Azure, and GCP

•Architect and implement up-to-date data platforms: Lakehouse (Databricks / Delta Lake), Cloud Warehouses (Snowflake, BigQuery, Synapse), and hybrid data meshes

•Design and govern scalable data pipelines using Apache Spark, dbt, Airflow, Azure Data Factory, AWS Glue, and Dataflow

•Drive DataOps and data engineering best practices: CI/CD for data, automated testing, lineage, and observability

•Ensure real-time and streaming data architectures using Kafka, Kinesis, or Azure Event Hubs where required

Data Architecture & Technical Leadershi p

•Define and enforce data architecture standards across Lakehouse, Data Vault 2.0, dimensional modelling, and data mesh patterns

•Lead cloud-native data platform design across AWS (Redshift, Lake Formation, Glue), Azure (Synapse Analytics, Purview, Fabric), and GCP (BigQuery, Dataplex, Vertex AI Feature Store)

•Oversee data governance, data quality frameworks, metadata management, and master data management (MDM) programs

•Evaluate and recommend data tools, frameworks, and accelerators to improve delivery speed and platform resilience





•Guide teams on advanced analytics patterns, semantic layer design, and self-serve BI enablement

Data Adoption Across Accounts

•Identify and drive high-impact data platform modernisation opportunities within existing and new accounts

•Enable delivery teams to adopt data-first engineering practices and cloud-native data tooling

•Embed data quality, lineage, and observability standards into every engagement from day one

Presales & Customer Engagement

•Lead data-focused solutioning, effort estimation, and proposal responses for RFPs and new opportunities

•Facilitate customer data discovery workshops, architecture design sessions, and executive briefings

•Build trusted advisor relationships with Chief Data Officers, VPs of Engineering, and Analytics leadership

•Articulate the value of modern data platforms in business terms — cost reduction, time-to insight, and data product

ROI

Capability Building & Team Growth

•Build and scale a high-performing team of data architects, data engineers, analytics engineers, and data governance leads

•Upskill teams on modern data stack tools: Databricks, Snowflake, dbt, Great Expectations, Apache Iceberg, and hyperscaler data services

•Establish an internal Data Centre of Excellence (CoE) with reusable assets, reference architectures, and playbooks

•Drive hiring, performance management, career development,



and succession planning within the practice

WHAT WE'RE LOOKING FOR

Must-Have

•15+ years in data engineering, data architecture, analytics, or cloud data platform delivery

•Proven hands-on experience designing and delivering Lakehouse, Data Warehouse, and Data Mesh architectures at scale

•Mandatory depth in modern data platforms and tooling:

•Cloud Data Warehouses: Snowflake, BigQuery, Azure Synapse, or Amazon Redshift

•Data Orchestration: Apache Airflow, Azure Data Factory, AWS Glue, or Prefect / Dagster

•Data Transformation: dbt (data build tool) — models, tests, documentation, and lineage

•Big Data Processing: Apache Spark (PySpark) on Databricks, EMR, or Dataproc

•Streaming: Kafka, AWS Kinesis, or Azure Event Hubs

•Strong command of cloud data ecosystems across AWS, Azure, and/or GCP

•Deep expertise in data governance, data quality (Great Expectations / Monte Carlo), and metadata management

•Track record leading multi-team data delivery programs and winning client confidence

•Strong presales and executive communication skills

You Will Stand Out If You Have

•Hands-on experience with Apache Iceberg, Delta Lake, or Apache Hudi for open table format architectures

•Familiarity with DataOps tooling: data contracts, automated data quality gates, and observability platforms

•Exposure to AI/ML feature engineering, Vertex AI Feature Store, or MLflow in a data delivery context

•Experience standing up a Data CoE or data practice from the ground up

•Background in IT services, consulting, or GCC environments with commercial accountability

•Certifications in Databricks, Snowflake, or hyperscaler data platforms (AWS / Azure/ GCP)

📌 Head of Data Practice & Delivery (Hyderabad)
🏢 Spot Your Leaders u0026 Consulting
📍 Hyderabad