AWS Engineer at Fractal Analytics, Bengaluru
AWS Engineer at Fractal Analytics in Bengaluru. Full-time. Apply with swipeandhired.
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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!
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