Cloud Data Transformation Practice Lead

Amdocs; Pune District; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

A leading technology firm is seeking a Cloud Data Transformation Practice Lead to architect modernization efforts for enterprise data platforms. Responsibilities include defining the transformation roadmap, leading migrations to cloud platforms like AWS, Azure, and GCP, and embedding AI/ML capabilities into data solutions. The ideal candidate has over 15 years of experience in data engineering and must possess strong programming skills in Python and Spark. This full-time position offers a competitive package and the opportunity to lead innovative data projects.

Qualifications

• 15+ years in data engineering with expertise in cloud platforms.
• Strong programming skills in Python and Spark.
• Proven experience with DataOps processes and tools.

Responsibilities

• Architect and deliver modernization of enterprise data platforms.
• Define and execute the data transformation roadmap.
• Lead migrations to various cloud services ensuring data security.

Skills

Data engineering expertise

AWS

Azure

GCP

Snowflake

Databricks

Python

Spark

ETL/ELT

DataOps

Tools

Prometheus

Grafana

ELK/EFK Stack

Datadog

CloudWatch

Azure Monitor

Job description

As the Cloud Data Transformation Practice Lead, you will architect and deliver the modernization of enterprise data platforms—migrating on-premises, structured, and unstructured databases to scalable, cloud-native solutions on AWS, Azure, GCP, Snowflake, and Databricks. You will define frameworks and reusable assets for efficient, secure, and analytics-ready data transformation, enabling advanced analytics, AI/ML, and business value acceleration.

Responsibilities

• Strategic Leadership: Define and execute the data transformation roadmap; drive business growth and practice differentiation.
• Reusable Assets & IP: Build and maintain reusable tools, accelerators, frameworks, and intellectual property for data migration, ETL/ELT, data modeling, and cloud-native pipelines.
• AI/ML & DataOps: Embed AI/ML capabilities into data solutions; champion DataOps practices (CI/CD, automated testing, monitoring, observability) for data workloads.
• Cloud Platform Expertise: Lead migrations to AWS, Azure, GCP, Snowflake, and Databricks; ensure best practices in data security, privacy, and compliance.
• Executive & Customer Engagement: Present technical solutions, transformation roadmaps, and business value to executives and customers; deliver technical briefings and workshops.
• RFPs, Proposals & SOWs: Actively participate in RFP responses, proposal development, and SOW creation for data transformation opportunities.
• Collaboration: Work closely with delivery, pre-sales/GTM and R&D teams to deliver integrated solutions.
• Mentorship: Lead and mentor teams, fostering a culture of innovation and continuous improvement.

Technical Skills Required

• 15+ years in data engineering, with deep expertise in AWS, Azure, GCP, Snowflake, and Databricks.
• Proven experience migrating on-premises structured/unstructured databases to cloud.
• Mastery of ETL/ELT, data modeling, and building scalable data pipelines (batch, streaming, real-time).
• Strong programming skills (Python AND Spark) and experience with cloud-native data services.
• Demonstrated experience with DataOps: CI/CD, data quality, lineage, and observability tools.
• Hands-on experience embedding AI/ML into data platforms and enabling advanced analytics.
• Data security, IAM, encryption, and regulatory compliance expertise.
• Leadership and consulting experience, with strong communication and executive presentation skills.
• hands of experience on Hyperscalers (Azure, AWS, GCP) Data services.

Data Monitoring & Observability Tools/Tech Stack

• Experience with monitoring and observability tools such as Prometheus, Grafana, ELK/EFK Stack, Datadog, CloudWatch (AWS), Azure Monitor, Google Cloud Operations Suite, OpenTelemetry, Great Expectations, Monte Carlo, and OpenLineage.

Nice-to-Have

• Certifications in AWS, Azure, GCP, Snowflake, or Databricks.
• Experience with open-source data engineering tools.
• Background in AI/ML, app modernization, or cloud security.

Seniority level

• Director

Employment type

• Full-time

Job function

• Consulting
• Software Development

Industries

• Software Development