AWS Data Engineer

Job Description

Dear Candidate, Greetings of the day!! I am Amutha and I'm reaching out to you regarding an exciting opportunity with TechMango. You can connect with me on LinkedIn?https://www.linkedin.com/in/amutha-valli-32611b289/?Or Email:[email protected] Techmango?Technology Services? is a full-scale software development services company founded in 2014 with a strong focus on emerging technologies. It holds a primary objective of delivering strategic solutions towards the goal of its business partners in terms of technology. We are a full-scale leading Software and Mobile App Development Company.?Techmango?is driven by the mantra ?Clients Vision is our Mission?. We have a tendency to stick on to the current statement. To be the technologically advanced & most loved organization providing prime quality and cost-efficient services with a long-term client relationship strategy.?We are operational in the USA - Chicago, Atlanta, Dubai - UAE, in India - Bangalore, Chennai, Madurai, Trichy. Role:??AWS?Data?Engineer Key Skills:?Data?Engineer,?Python,?AWS?services,?python, SQL, ETL, pyspark Experience: 3 to 8 Yrs Location:?Madurai Mode : Hybrid / WFO Job Title:??AWS?Data?Engineer About the Role: We?re looking for a seasoned?AWS?Data?Engineer ?to join our Engineering organization and take ownership of the cloud-based systems that power our most critical?data-driven decisions. You?ll design, architect, and maintain high-performance, scalable?data?pipelines and cloud?data?warehouses using?AWS-native services such as Redshift, Glue, S3, Lambda, and Step Functions. This is a high-impact role ideal for someone who thrives in solving complex?data?challenges, optimizing distributed systems, and being the go-to expert in a collaborative and high-performance engineering team. What You Will Do: Architect, build, and maintain robust and scalable?data?pipelines using?AWS?services. Implement performant and reliable ETL/ELT processes that handle large volumes of structured and unstructured?data. Enforce and monitor?data?SLAs to ensure freshness, reliability, and availability of datasets across environments. Collaborate with engineering, product, and analytics teams to transform business requirements into robust?data?models and pipelines. Proactively identify and resolve bottlenecks,?data?quality issues, and system inefficiencies. Implement schema versioning,?data?lineage tracking, and database change management practices. Define and enforce best practices for?data?governance, access control, observability, and compliance. Contribute to CI/CD workflows and infrastructure as code practices using tools like CloudFormation or Terraform. What You Will Bring: 4+ years?of experience in?data?engineering or backend systems development, with a strong focus on cloud-based architectures. Deep expertise in?AWS?data?ecosystem?especially Redshift, Glue, S3, Athena, Lambda, Step Functions, and CloudWatch. Strong background in?SQL performance tuning, schema design, indexing, and partitioning?strategies for large datasets. Experience maintaining?data?freshness SLAs?and end-to-end ownership of production pipelines. Hands-on experience with?Python?(or PySpark), T-SQL, and scripting automation for?data?ingestion and transformation. Solid understanding of?relational and dimensional?data?modeling, normalization, and schema evolution. Experience with?source control systems?(e.g., Git, Bitbucket) and CI/CD pipelines for?data?infrastructure. Track record of transforming complex business requirements into reliable and scalable?data?solutions. Experience with?data?governance, security, and?compliance frameworks?(e.g., HIPAA, GDPR) is a plus. Familiarity with monitoring and observability tools (e.g., CloudWatch, Datadog, or Prometheus). Bonus: Exposure to Snowflake or MSSQL in hybrid cloud environments. Nice to Have: AWS?certifications such as?AWS?Certified?Data?Analytics,?Solutions Architect, or?DevOps Engineer. Experience with?Apache Airflow,?dbt, or other?data?orchestration tools. Familiarity with?Kafka,?Kinesis, or other streaming technologies. Understanding of?data?mesh?or?data?lakehouse?architectures