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ATT Communication Services
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Lead Data/AI Engineering

Lead Data/AI Engineering

ATT Communication Services

15 - 20 years

20 - 25 Lacs

bengaluru

Posted:1 hour ago| Platform:

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Skills Required

telecom performance tuning automation project management workflow informatica apache troubleshooting sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Design, Development, Testing, and Deployment: Drive the development of scalable Data & AI warehouse applications by leveraging software engineering best practices such as automation, version control, and CI/CD. Implement comprehensive testing strategies to ensure reliability and optimal performance. Manage deployment processes end-to-end, effectively addressing configuration, environment, and security concerns.

Engineering and Analytics: Transform Data Warehouse and AI use case requirements into robust data models and efficient pipelines, ensuring data integrity by applying statistical quality controls and advanced AI methodologies.
API & Microservice Development: Design and build secure, scalable APIs and microservices for seamless data integration across warehouse platforms, ensuring usability, strong security, and adherence to best practices.
Platform Scalability & Optimization: Assess and select the most suitable technologies for cloud and on-premises data warehouse deployments, implementing strategies to ensure scalability, robust performance monitoring, and cost-effective operations.
Lead : Lead the execution of complex data engineering and AI projects to solve critical business problems and deliver impactful results.
Technologies: Leverage deep expertise in Data & AI technologies (such as Spark, Kafka, Databricks, and Snowflake), programming (including Java, Scala, Python, and SQL), API integration patterns (like HTTP/REST and GraphQL), and leading cloud platforms (Azure, AWS, GCP) to design and deliver data warehousing solutions.

Shift timing (if any): 12:30 PM to 9:30 PM IST

Location / Additional Location (if any): Bangalore, Hyderabad

Overall Experience:

Typically requires a minimum 15 years of progressive experience in data engineering, data architecture, or related fields.
Demonstrated experience leading complex data projects, managing teams, and delivering end-to-end data solutions in large or matrixed organizations is highly valued.
Experience with cloud data platforms, big data technologies, and implementing best practices in data governance and DevOps is strongly preferred.

Primary / Mandatory skills:

Delivery: Proven experience in managing and delivering complex data engineering and AI solutions for major business challenges.
Data Architecture & Modeling:
Expertise in designing scalable, high-performance data architectures (e.g., data warehouses, data lakes, data marts) and creating robust data models.
ETL/ELT Development:
Advanced skills in building, optimizing, and maintaining data pipelines using modern ETL/ELT tools (e.g., Informatica, Talend, dbt, Azure Data Factory).
Cloud Platforms:
Proficiency with cloud data services and platforms such as AWS, Azure, or Google Cloud (e.g., Redshift, Snowflake, Databricks, BigQuery).
Programming Languages:
Strong coding ability in SQL and at least one general-purpose language (e.g., Python, Scala, Java).
Big Data Technologies:
Experience with distributed data processing frameworks (e.g., Spark, Hadoop) and real-time streaming tools (e.g., Kafka).
Data Governance & Quality:
Knowledge of data governance practices, data lineage, data cataloging, and implementing data quality checks.
CI/CD & Automation:
Experience in automating data workflows, version control (e.g., Git), and deploying CI/CD pipelines for data applications.
Analytics & AI/ML Integration:
Ability to support advanced analytics and integrate machine learning pipelines with core data platforms.
Leadership & Collaboration:
Proven track record in leading teams, mentoring engineers, and collaborating with business, analytics, and IT stakeholders.
Problem Solving & Communication:
Strong analytical, troubleshooting, and communication skills to translate business needs into technical solutions.

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Lead Data/AI Engineering