AWS - Data Engineer

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

Or Email:

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: 4 to 10 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