AWS Engineer

Fractal Analytics Ltd.; Bengaluru; Vor Ort; INR 1.200.000 - 2.400.000; Vollzeit

Zusammenfassung

Fractal Analytics Ltd. is seeking a highly motivated Data Engineer with 3-4 years of hands-on experience in AWS Databricks to join our data platform team in Bengaluru. You will design, build, and maintain scalable data pipelines and data solutions within the AWS cloud environment.

The role requires strong PySpark and SQL skills, experience with Delta Lake, and familiarity with AWS services. You will collaborate with data scientists, analysts, and business stakeholders to deliver high-performance

Qualifikationen

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline.
• 3-4 years of experience in Data Engineering or a similar role.
• Strong hands-on experience with AWS Databricks.
• Good proficiency in PySpark and SQL for large-scale data processing.
• Experience working with Delta Lake and modern lakehouse concepts.
• Familiarity with AWS services such as Amazon S3, RDS, Glue, Lambda, and Redshift.
• Knowledge of batch and streaming data architectures.
• Experience with workflow orchestration, monitoring, and debugging of pipelines.
• Understanding of version control and CI/CD practices.
• Awareness of data security, governance, and metadata management principles.
• Strong analytical, problem-solving, and communication skills.

Aufgaben

• Design, develop, test, and deploy scalable ETL/ELT pipelines using AWS Databricks, PySpark, and SQL.
• Build and maintain robust data pipelines for ingesting and processing structured and unstructured data from multiple sources such as Amazon S3, Amazon RDS, APIs, and external platforms.
• Implement and manage Delta Lake solutions to support both batch and streaming data processing.
• Optimize Spark workloads for performance, scalability, and cost efficiency.
• Ensure data quality, consistency, reliability, and integrity through validations, monitoring, exception handling, and reconciliation checks.
• Collaborate with cross-functional teams including data analysts, data modelers, architects, and business stakeholders to support reporting, analytics, and downstream consumption.
• Support orchestration and scheduling of pipelines using tools such as AWS Glue Workflows, Apache Airflow, or AWS Step Functions.
• Participate in CI/CD implementation and code deployment processes using Git, AWS CodePipeline, and CodeBuild.
• Apply best practices related to data governance, metadata management, security, and access control.
• Support production issue resolution, ad hoc data requests, and continuous improvement of the data platform.

Kenntnisse

PySpark

SQL

Communication

Analytical thinking

Problem-solving

Team collaboration

Data governance

Ausbildung

Bachelor's degree in Computer Science / Information Systems / Engineering

Tools

AWS Databricks

Delta Lake

Apache Airflow

AWS Glue

AWS Step Functions

Git

CodePipeline

CodeBuild

Jobbeschreibung

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business.

Job Description Role Summary

We are looking for a highly motivated Data Engineer with 3-4 years of hands-on experience in AWS Databricks to join our data platform team. The role involves working closely with data scientists, analysts, architects, and business stakeholders to design, build, and maintain scalable, high-performance data pipelines and data solutions within the AWS cloud environment. The ideal candidate should have strong expertise in Databricks, PySpark, SQL, Delta Lake, and AWS data services, along with a good understanding of modern data engineering practices, orchestration, and data governance.

Key Responsibilities

• Design, develop, test, and deploy scalable ETL/ELT pipelines using AWS Databricks, PySpark, and SQL.
• Build and maintain robust data pipelines for ingesting and processing structured and unstructured data from multiple sources such as Amazon S3, Amazon RDS, APIs, and external platforms.
• Implement and manage Delta Lake solutions to support both batch and streaming data processing.
• Optimize Spark workloads for performance, scalability, and cost efficiency.
• Ensure data quality, consistency, reliability, and integrity through validations, monitoring, exception handling, and reconciliation checks.
• Collaborate with cross-functional teams including data analysts, data modelers, architects, and business stakeholders to support reporting, analytics, and downstream consumption.
• Support orchestration and scheduling of pipelines using tools such as AWS Glue Workflows, Apache Airflow, or AWS Step Functions.
• Participate in CI/CD implementation and code deployment processes using Git, AWS CodePipeline, and CodeBuild.
• Apply best practices related to data governance, metadata management, security, and access control.
• Support production issue resolution, ad hoc data requests, and continuous improvement of the data platform.

Required Skills and Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline.
• 3-4 years of experience in Data Engineering or a similar role.
• Strong hands-on experience with AWS Databricks.
• Good proficiency in PySpark and SQL for large-scale data processing.
• Experience working with Delta Lake and modern lakehouse concepts.
• Familiarity with AWS services such as Amazon S3, Amazon RDS, AWS Glue, AWS Lambda, and Amazon Redshift.
• Knowledge of batch and streaming data architectures.
• Experience with workflow orchestration, monitoring, and debugging of pipelines.
• Understanding of version control and CI/CD practices.
• Awareness of data security, governance, and metadata management principles.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience in building data pipelines in enterprise-scale cloud data platforms.
• Familiarity with real-time / streaming frameworks and event-driven architectures.
• Exposure to data quality frameworks, reconciliation processes, and operational monitoring.
• Working knowledge of infrastructure automation and cloud deployment best practices.
• Experience collaborating in agile delivery environments.

Key Competencies

• Strong problem-solving orientation
• Attention to detail and focus on data quality
• Ability to work in a fast-paced, collaborative environment
• Good stakeholder communication and coordination skills
• Ownership mindset with a focus on delivery excellence

Nice to Have

• Experience with data modeling and analytics enablement
• Exposure to DevOps and platform engineering practices

Certification in AWS or Databricks technologies

Why Join Us

This role offers the opportunity to work at the forefront of cloud-based data engineering, partnering with talented data scientists, analysts, and architects to build scalable, high-impact data solutions on AWS Databricks. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

At Fractal, towards our goal of "powering every human decision in the enterprise", our partnerships and alliances help in creating and delivering a compelling suite of solutions to unlock value. We partner with companies from around the globe, leaders in their respective fields. With Fractals expertise in artificial intelligence, design, engineering, and digital transformation, combined with the data, technology, and software platforms from our partners, we create cutting-edge solutions to problems in the business world. We understand how critical and timely decision triggers, and information, empower our clients to create, unlock, deliver, and realize value. Together with our partners, our goal is to serve each client in their end-to-end data-to-decision journey.