As a Senior Data Engineer, you will play a crucial role in designing, implementing, and maintaining our data infrastructure. you'll work with modern data engineering technologies and cloud platforms to build scalable ETL pipelines, optimize data processing workflows, and ensure data quality and reliability across our systems. This role extends significantly into the ML domain, where you'll be responsible for building and maintaining feature engineering pipelines that power various ML models across the organization. you'll work on real-time feature generation systems, deploy and maintain ML model infrastructure, and ensure seamless integration between data pipelines and ML workflows. Your work will directly impact model performance and enable data scientists to focus on model development rather than infrastructure concerns.

Responsibilities

Partner closely with business stakeholders to understand and translate data warehouse requirements into technical solutions

Provide comprehensive support for data warehouse initiatives including requirements gathering, solution design, and implementation

Optimize data warehouse performance through query optimization, indexing strategies, and architectural improvements

Design, develop, and maintain robust ETL/ELT pipelines using modern data engineering tools

Implement real-time and batch data processing solutions to meet business requirements

Develop and maintain data models and DataMart solutions for analytics and reporting needs

Deploy and maintain ML model infrastructure ensuring scalability and reliability

Requirements:

3-6 years of experience in Data Engineering

Strong expertise in distributed computing and advanced problem-solving/analytical skills

Deep understanding of data warehouse design, optimization, and performance tuning

Expertise in Python, SQL and NoSQL databases

In-depth experience in Could services, preferably AWS (EMR, S3, Redshift, MSK)

Expertise in Data engineering tech stack like Spark (PySpark), Airflow, Debezium, Hadoop

Experience in data modelling, DataMart development

Understanding of ML model deployment and maintenance workflows with feature store architectures and best practices

Good to Have - Experience in setting up and working with On-premises Data Engineering tech stack

What we offer

A positive, get-things-done workplace

A dynamic, constantly evolving space (change is par for the course important you are comfortable with this).

An inclusive environment that ensures we listen to a diverse range of voices when making decisions.

Ability to learn cutting edge concepts and innovation in an agile start-up environment with a global scale.

Access to 5000+ training courses accessible anytime/anywhere to support your growth and development (Corporate with top learning partners like Harvard, Coursera, Udacity).

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Senior Data Engineer