Introduction
Are you a data enthusiast with a passion for building robust and scalable data pipelines that power cutting-edge AI and analytics solutions? Fractal, a global leader in artificial intelligence and analytics, is seeking talented Data Engineers to join its innovative teams. This is an exceptional opportunity to work with vast datasets, leverage modern cloud technologies, and contribute to the foundation of AI-driven decision-making for clients across diverse industries. If you thrive on transforming raw data into actionable insights and enjoy solving complex data challenges, Fractal offers a dynamic and impactful career.
Roles and Responsibilities
As a Data Engineer at Fractal, you will be responsible for designing, building, and maintaining the data infrastructure and pipelines that feed the firm’s analytical models and AI applications. Your key responsibilities may include:
- Designing, developing, and optimizing ETL/ELT processes to ingest, transform, and load large volumes of data from various sources into data lakes and data warehouses.
- Building and managing scalable data pipelines using big data technologies (e.g., Spark, Hadoop) and cloud data services (e.g., AWS Glue, Azure Data Factory, Google Cloud Dataflow).
- Implementing data models and schemas optimized for performance and analytics.
- Ensuring data quality, consistency, and reliability across all data assets.
- Collaborating closely with data scientists, ML engineers, and business analysts to understand data requirements and deliver efficient data solutions.
- Troubleshooting and resolving data-related issues, pipeline failures, and performance bottlenecks.
- Automating data workflows, monitoring data health, and setting up alerts for anomalies.
- Contributing to the adoption of DataOps principles and best practices for data governance and security.
- Evaluating and integrating new data technologies and tools to enhance the data platform.
Salary and Benefits
Fractal offers a competitive salary and comprehensive benefits package for Data Engineers, aligning with industry standards for a leading AI and analytics firm in India. While specifics can vary by experience and role level, typical offerings include:
- Competitive base salary commensurate with experience and expertise.
- Performance-linked incentives or bonuses.
- Comprehensive health, life, and accident insurance coverage.
- Provident Fund (PF) and Gratuity benefits as per Indian regulations.
- Paid time off, including holidays and vacation.
- Opportunities for continuous learning and professional development, including certifications in cloud data platforms and big data technologies.
- Employee assistance programs and wellness initiatives.
- A collaborative and intellectually stimulating work environment focused on innovation in AI.
- Exposure to diverse client industries and complex data challenges.
- Potential for career growth within data engineering or into related roles like MLOps or data architecture.
Application Process
Ready to build the data backbone for cutting-edge AI? Here’s how to apply for a Data Engineer position at Fractal:
- Online Application: Visit the Fractal Careers website and search for “Data Engineer” or similar roles.
- Detailed Resume/CV: Prepare a comprehensive resume highlighting your experience with programming languages (Python, Scala, Java), SQL, big data frameworks (Spark, Hadoop), cloud data services (AWS, Azure, GCP), data warehousing concepts, and ETL/ELT tools. Highlight any relevant projects, certifications, or contributions to data initiatives.
- Technical Assessments (if applicable): You may be asked to complete online coding challenges focusing on data manipulation, SQL queries, and algorithmic problem-solving.
- Interview Scheduling: Successful candidates will be invited for interview rounds.
Interview Process
The interview process for a Data Engineer at Fractal is typically thorough, designed to assess your technical expertise, problem-solving skills, and understanding of data ecosystems. It generally includes:
- HR Screen: An initial discussion about your background, career aspirations, and cultural fit within Fractal’s AI-driven environment.
- Technical Phone Screen(s): These rounds will likely cover SQL queries, Python programming, data warehousing concepts, and basic big data principles.
- Onsite/Virtual Technical Interviews (multiple rounds, often 3-5): Expect several in-depth technical discussions and problem-solving sessions:
- SQL & Data Modeling: Complex SQL queries, database design, normalization/denormalization, and schema design for analytical workloads.
- Programming & Data Structures: Coding challenges in Python or Scala, focusing on efficient data processing, algorithms, and data structures.
- Big Data Technologies: In-depth discussion of Spark, Hadoop, Kafka, or other relevant distributed data processing frameworks.
- Cloud Data Services: Your experience and knowledge of specific cloud data services (e.g., AWS S3, Redshift, Glue, Azure Synapse, GCP BigQuery, Dataflow).
- ETL/ELT Design: Designing end-to-end data pipelines for specific use cases, discussing tools, challenges, and best practices.
- Data Quality & Governance: How you approach ensuring data quality, handling data inconsistencies, and understanding data governance principles.
- Behavioral Questions: Assessing your teamwork, communication, and approach to complex data challenges and collaboration.
Conclusion
Joining Fractal as a Data Engineer offers an exciting opportunity to be at the heart of AI and analytics innovation, building the foundational data systems that enable transformative insights. If you are a skilled data professional with a passion for scalable architecture, robust pipelines, and clean data, Fractal provides an excellent platform to grow your expertise and contribute to high-impact AI solutions. Apply today and help power the future of intelligent decision-making!
