Cloud Data Transformation Practice Lead

4 days ago

Pune, India Amdocs Full time

Role Summary 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. Key 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.

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