Data Engineer

Overview:

We are looking for a Data Engineer with strong experience in designing, building, and maintaining scalable data pipelines and data platforms. The ideal candidate will work closely with data scientists, analysts, and engineering teams to ensure reliable, high-quality data for analytics and AI/ML use cases.

Key Responsibilities:

Design, develop, and optimize scalable data pipelines (batch and real-time)

Build and maintain data warehouses, data lakes, and ETL/ELT workflows

Ensure data quality, integrity, and reliability across systems

Work with large-scale structured and unstructured datasets

Optimize data processing for performance and cost efficiency

Collaborate with Data Scientists and Analysts to support analytics and ML workloads

Implement data governance, security, and compliance best practices

Monitor, troubleshoot, and improve existing data infrastructure

Mentor junior data engineers and contribute to architectural decisions

Required Skills & Qualifications:

3+ years of experience in Data Engineering

Strong programming skills in Python and/or SQL

Experience with ETL/ELT tools (Airflow, dbt, Informatica, etc.)

Hands-on experience with data warehouses (BigQuery, Snowflake, Redshift, or similar)

Experience with cloud platforms (AWS / GCP / Azure)

Strong understanding of database concepts, data modeling, and schema design

Experience handling large-scale data pipelines

Familiarity with CI/CD and version control (Git)

Good to Have:

Experience with streaming technologies (Kafka, Spark Streaming, Flink)

Knowledge of Big Data frameworks (Spark, Hadoop)

Exposure to MLOps / analytics engineering

Experience with NoSQL databases (MongoDB, Cassandra)

Cloud certifications (AWS/GCP/Azure Data or Engineering track)

Soft Skills:

Strong problem-solving and analytical skills

Excellent communication and collaboration abilities

Ability to work independently and take ownership

Mentorship and leadership mindset