Senior Data Engineer - Data lakehouse

Job Title: Senior

Job Location:

Working Mode:

Experience:

Working Hours:

Interview Process: 2-

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

Requirement Summary:

We are seeking a highly skilled and motivated Senior Data Engineer with overall 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)

Please share me the below details:

Total Experience:

Relevant Experience in Data Engineering:

Exp in Data Lakehouse:

Exp in AWS:

Exp in AWS Glue ETL:

Exp in Python & Pyspark:

Reason for the Job change:

Current Company:

Current Location:

Preferred Location:

CCTC:

ECTC:

Notice Period:

Are you able to join us with in 15-20 Days Yes/No:

If You're serving notice Pls mention the Last working date:

Marital Status & Your Native Location:

If You are Holding any offer, pls mention the CTC & Job Location:

Available for Virtual Interview on Weekdays Yes/No: