Senior Data Engineer – AWS & Data Lakehouse Specialist

Hi, 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: amutha.m@techmango.net
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.Techmangohttps://www.techmango.net/

Job Title: Senior Data Engineer – AWS & Data Lakehouse Specialist

Requirement Summary:
We are seeking a highly skilled and motivated Senior Data Engineer with overall 7-8 years of
experience and 4–5 years of hands-on experience in building scalable data solutions on AWS. The ideal candidate will be proficient in Python, PySpark, and AWS Glue, with a strong understanding of Data Lakehouse architecture—especially the medallion model. You will play a key role in designing, developing, and optimizing data pipelines, ensuring data quality, and implementing infrastructure as code using Terraform.
Key Responsibilities:

• Design and implement scalable ETL/ELT pipelines using AWS Glue and PySpark

• Develop and maintain data workflows using AWS Glue DataBrew and AWS Data Quality services

• Architect and manage Data Lakehouse solutions following the medallion architecture

• (Bronze, Silver, Gold layers)

• Optimize data lake performance (Parquet formats, partitioning strategies, DPU tuning)

• Implement S3 data encryption and security best practices

• Automate infrastructure provisioning using Terraform (IaC)

• Collaborate with data analysts, scientists, and business stakeholders to deliver clean, reliable data

• Integrate and manage DBT workflows for data transformation and modeling (preferred)

• Monitor, troubleshoot, and enhance data pipeline reliability and performance

Required Skills & Qualifications:

• 4–5 years of relevant experience in data engineering with a focus on AWS

• Strong proficiency in SQL, Python and PySpark

• Hands-on experience with AWS Glue ETL, Glue DataBrew, and AWS Data Quality

• Proven expertise in building and managing Data Lakehouse architectures using medallion layering

• Deep understanding of Parquet file formats, partitioning, and DPU configuration for performance tuning

• Experience with S3 encryption and data security protocols

• Solid grasp of Infrastructure as Code using Terraform

• Familiarity with DBT for data transformation and modeling (preferred)

• Strong problem-solving skills and ability to work independently and collaboratively

Preferred Qualifications:

• AWS certifications (e.g., AWS Certified Data Analytics, AWS Solutions Architect)

• Experience with CI/CD pipelines and DevOps practices

• Exposure to data governance and cataloging tools (e.g., AWS Glue Catalog, Lake

• Formation)

Job Type: Full-time

Pay: ₹2,500,000.00 - ₹3,500,000.00 per year

Application Question(s):

• Overall work experience:
• How many years of experience do you have in AWS?
• How many years of experience do you have in SQL, Python and PySpark?
• How many years of experience do you have in AWS Glue ETL, Glue DataBrew, and AWS Data Quality?
• How many years of experience do you have in Data Lakehouse ?
• May I know your last working date:
• CTCC:
• ETCC:

Work Location: In person