Data Platform Engineer
Accenture
- Location
- Onsite (Hyderabad, Telangana)
- Employment
- Full-time
- Level
- Senior Level
Posted 2 weeks ago
About the role
Accenture is a global professional services firm helping organizations build their digital core and drive innovation through AI and technology. This role involves designing and optimizing scalable data platforms and pipelines to support enterprise-grade analytics and business transformation.
Skills
Databricks
PySpark
Apache Spark
Big Data
Data Pipeline Architecture
ETL/ELT
AWS
Azure
Google Cloud Platform
Python
SQL
Apache Kafka
Data Security
Data Governance
Real-Time Data Processing
Cloud Data Platforms
Full job details
Project Role : Data Platform Engineer
Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
Must have skills : Databricks Unified Data Analytics Platform
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: Seeking a forward-thinking professional with an AI-first mindset to design, develop, and deploy enterprise-grade solutions using Generative and Agentic AI frameworks that drive innovation, efficiency, and business transformation. As a Data Platform Engineer, you will assist with the data platform blueprint and design, collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models. You will play a crucial role in shaping the data platform components.
Roles and Responsibilities:
Lead the design, development, and optimization of complex data pipelines, ensuring high performance and scalability using PySpark, Spark, and Big Data technologies.
Architect data engineering solutions across major cloud platforms like AWS, Azure, or GCP, enabling smooth and secure data ingestion, transformation, and storage.
Lead efforts to design and build modular, reusable ETL/ELT pipelines to integrate data from various sources into cloud-based data lakes and data warehouses.
Collaborate closely with cross-functional teams, including data scientists, analysts, and other engineering teams to develop and maintain large-scale data processing systems.
Guide and mentor junior engineers in best practices for data engineering, cloud technologies, and big data solutions.
Optimize and tune Spark and big data processing jobs to handle high-volume data efficiently and at scale.
Ensure data security, privacy, and governance are maintained by enforcing best practices and policies across cloud platforms.
Implement automated data testing and monitoring solutions to ensure data quality and pipeline reliability.
Drive initiatives for real-time data processing, batch jobs, and analytics pipelines to support both operational and analytical needs.
Advocate for continuous improvement, researching new tools, and technologies to drive data engineering excellence.
Required Skills & Qualifications:
Proven experience with AWS, Azure, or GCP in designing data engineering workflows and solutions.
Expert-level knowledge of PySpark, Spark, and Big Data technologies.
Extensive experience in data pipeline architecture, design, and optimization.
Strong hands-on experience with large-scale ETL/ELT processes and integrating data into cloud-based platforms like S3, Blob Storage, BigQuery, and Redshift.
Proficiency in Python, SQL, and scripting for data pipeline development.
Ability to work with real-time data streaming tools like Kafka and batch processing tools.
Experience leading cross-functional teams in the implementation of cloud-based data platforms and workflows.
Solid understanding of data security, compliance, and governance in a cloud environment.
Nice to Have:
Familiarity with dbt (Data Build Tool) for managing data transformation and data quality.
Exposure to CI/CD pipelines, DevOps practices, and containerization technologies (Docker, Kubernetes).
Certifications or experience with data tools like Apache Airflow, Fivetran, Informatica, or Talend.
Experience with analytics and BI tools like Power BI, Tableau, or Looker for visualization over cloud-based data platforms.
Educational Qualification:
15 years full time education is required.
15 years full time education
Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
Must have skills : Databricks Unified Data Analytics Platform
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: Seeking a forward-thinking professional with an AI-first mindset to design, develop, and deploy enterprise-grade solutions using Generative and Agentic AI frameworks that drive innovation, efficiency, and business transformation. As a Data Platform Engineer, you will assist with the data platform blueprint and design, collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models. You will play a crucial role in shaping the data platform components.
Roles and Responsibilities:
Lead the design, development, and optimization of complex data pipelines, ensuring high performance and scalability using PySpark, Spark, and Big Data technologies.
Architect data engineering solutions across major cloud platforms like AWS, Azure, or GCP, enabling smooth and secure data ingestion, transformation, and storage.
Lead efforts to design and build modular, reusable ETL/ELT pipelines to integrate data from various sources into cloud-based data lakes and data warehouses.
Collaborate closely with cross-functional teams, including data scientists, analysts, and other engineering teams to develop and maintain large-scale data processing systems.
Guide and mentor junior engineers in best practices for data engineering, cloud technologies, and big data solutions.
Optimize and tune Spark and big data processing jobs to handle high-volume data efficiently and at scale.
Ensure data security, privacy, and governance are maintained by enforcing best practices and policies across cloud platforms.
Implement automated data testing and monitoring solutions to ensure data quality and pipeline reliability.
Drive initiatives for real-time data processing, batch jobs, and analytics pipelines to support both operational and analytical needs.
Advocate for continuous improvement, researching new tools, and technologies to drive data engineering excellence.
Required Skills & Qualifications:
Proven experience with AWS, Azure, or GCP in designing data engineering workflows and solutions.
Expert-level knowledge of PySpark, Spark, and Big Data technologies.
Extensive experience in data pipeline architecture, design, and optimization.
Strong hands-on experience with large-scale ETL/ELT processes and integrating data into cloud-based platforms like S3, Blob Storage, BigQuery, and Redshift.
Proficiency in Python, SQL, and scripting for data pipeline development.
Ability to work with real-time data streaming tools like Kafka and batch processing tools.
Experience leading cross-functional teams in the implementation of cloud-based data platforms and workflows.
Solid understanding of data security, compliance, and governance in a cloud environment.
Nice to Have:
Familiarity with dbt (Data Build Tool) for managing data transformation and data quality.
Exposure to CI/CD pipelines, DevOps practices, and containerization technologies (Docker, Kubernetes).
Certifications or experience with data tools like Apache Airflow, Fivetran, Informatica, or Talend.
Experience with analytics and BI tools like Power BI, Tableau, or Looker for visualization over cloud-based data platforms.
Educational Qualification:
15 years full time education is required.
15 years full time education
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.