Title:We are looking for a seasoned Senior Python Developer with deep expertise in building scalable, cloud-native data solutions on AWS and the Databricks Lakehouse Platform. You will work alongside data engineers, architects, and product teams to design and deliver robust pipelines, APIs, and analytics products that power critical business decisions.

Job Description:

Required Skills &; Experience

Core Python & Engineering

7–10 years of professional Python development experience.

Deep proficiency with Python 3.x: OOP, design patterns, async programming, and

performance tuning.

Experience with web frameworks such as FastAPI, Flask, or Django.

Strong grasp of data structures, algorithms, and distributed systems.

Hands-on experience with SQL and NoSQL databases (PostgreSQL, MySQL, DynamoDB,

etc.).

Amazon Web Services (AWS)

Hands-on production experience with S3, Lambda, EC2, RDS, Glue, EMR, Step Functions,

and CloudWatch.

Solid understanding of AWS IAM, VPC, and cloud security best practices.

Deploying and managing containerised workloads on ECS, EKS, or Serverless frameworks.

Infrastructure-as-Code using Terraform and/or AWS CloudFormation.

Databricks &; Big Data

Hands-on experience with Databricks Workspace, Clusters, Jobs, and Notebooks.

Proficiency in PySpark for large-scale batch and streaming data processing.





Working knowledge of Delta Lake: ACID transactions, time travel, and schema evolution.

Familiarity with medallion architecture (Bronze / Silver / Gold) and data lakehouse design

patterns.

Exposure to Databricks Unity Catalog, MLflow, and Feature Store is a plus.

DevOps &; Collaboration

Robust Git workflow: branching strategies, pull requests, and code review discipline.

CI/CD experience with GitHub Actions, Jenkins, or Azure DevOps.

Docker containerisation; Kubernetes familiarity is advantageous.

Proven ability to work effectively in Agile/Scrum environments.

Good to Have

AWS Certified Developer – Associate or Solutions Architect certification.

Databricks Certified Associate or Professional certification.

Experience with streaming platforms such as Apache Kafka or AWS Kinesis.

Exposure to ML frameworks (scikit-learn, TensorFlow, PyTorch) or MLOps tooling.

Knowledge of dbt (data build tool) for transformation and data modelling workflows.

Prior experience in a consulting or product-based technology organisation.

Educational Qualifications

Bachelor’s or master’s degree in computer science, Engineering, or a related discipline.

Equivalent industry certifications or demonstrable experience will be considered.

📌 AWS Data Engineer (New Delhi)
🏢 TENARAI TECHNOLOGIES PRIVATE
📍 New Delhi