Job Description

:

Key Responsibilities:

Data Engineering and Integration:

Design, develop, and optimize scalable data pipelines and ETL processes using

Palantir Foundry

for data integration, transformation, and creating data models to support analytics and business use cases. Build and manage APIs and microservices using

Python

and

Java

to integrate data across systems and manage data processing and application logic.

Data Modeling and Architecture:

Design and implement robust, scalable, and efficient data models in Palantir Foundry. Collaborate with data architects to define data governance, data lineage, and data quality standards. Develop and maintain reusable pipelines and templates for data transformation and enrichment.

Azure Cloud Expertise:

Utilize

Azure Synapse

,

Azure Data Lake

, and

Azure Storage

for data storage and processing. Implement secure and efficient data workflows on Azure, ensuring compliance with organizational and regulatory policies. Monitor and troubleshoot Azure data pipelines for performance optimization.

Programming and Automation:

Write clean, maintainable, and efficient code in

Python

and

Java

for data processing, automation, and integration tasks. Develop scripts to automate repetitive tasks and improve overall system efficiency. Hands on Experience on

Snowflake

in writing procedures / functions, Snowpipe, Data Pipelines, Data Transformation.

Collaboration and Stakeholder Engagement:

Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights. Provide technical support and training on Palantir Foundry to internal teams. Participate in Agile development processes and collaborate with DevOps teams to ensure seamless deployment.

Performance Monitoring and Optimization:

Monitor data pipelines and applications for reliability, scalability, and performance. Implement best practices for error handling, logging, and alerting to ensure system stability.

Required Skills and Qualifications:

Technical Expertise:

+ Proficiency in

Palantir Foundry

for data integration, modeling, and pipeline development.
+ Strong programming skills in

Python

and

Java

.
+ Hands-on experience with

Azure Data Engineering

tools (e.g., Azure Data Factory, Databricks, Synapse, Data Lake, etc.).
+ Solid understanding of data structures, algorithms, and software engineering principles.

Data Engineering Skills:

+ Experience in building and optimizing ETL/ELT pipelines for large-scale data processing.
+ Proficiency in SQL for data querying and transformation.
+ Familiarity with data governance, data lineage, and data security practices.

Cloud Expertise:

+ Strong knowledge of Azure cloud services and infrastructure for data engineering.
+ Experience with CI/CD pipelines, containerization (e.g., Docker), and orchestration tools (e.g., Kubernetes).

Problem Solving and Collaboration:

+ Excellent problem-solving skills and ability to troubleshoot complex issues in data systems.
+ Strong communication skills to collaborate effectively with technical and non-technical stakeholders.

Preferred Qualifications:

Certification in

Palantir or

Microsoft Azure Data Engineering

or related cloud certifications. Experience in working in Agile/Scrum environments.

Weekly Hours:

40

Time Type:

Regular

Location:

Bangalore, Karnataka, India
It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.