Senior Data Platform Engineer — AI‑Driven Analytics

Akaasa Technologies; New York (NY); On-site; USD 99,000 - 135,000; Full time

Job summary

Akaasa Technologies is seeking a Senior Data Engineer to design, develop, and optimize scalable data platforms powering analytics, ML, and AI-driven solutions. You will work with Databricks, Spark, Delta Lake, Snowflake, Kafka, and AWS, contributing to GenAI, LLMs, RAG, and AI-assisted engineering.

The role emphasizes data quality, governance, and enterprise-scale data engineering across batch and streaming pipelines, with cloud-native, cost-efficient architectures.

Qualifications

• Bachelor's or Master's degree in Computer Engineering, Computer Science, Information Systems, or a related field.
• 8+ years of experience in software engineering, data engineering, or big data platform development.
• Strong experience designing and implementing enterprise-scale data pipelines.
• Hands-on expertise with Python, PySpark, Spark SQL, SQL, Kafka, Databricks, Delta Lake, Snowflake, Hive.

Responsibilities

• Design, build, and maintain scalable batch and real-time data pipelines.
• Develop and optimize ingestion, transformation, and processing frameworks for diverse datasets.
• Implement modern Lakehouse architectures using Databricks, Delta Lake, and Bronze–Silver–Gold patterns.
• Build data solutions for analytics, reporting, and machine learning.
• Ensure data quality, governance, lineage, security, and compliance.

Skills

8+ years experience in data/software

Analytical problem solving

Education

Bachelor's or Master's degree (CS/Engineering/IS)

Tools

Python

PySpark

Spark SQL

SQL

Kafka

Databricks

Delta Lake

Snowflake

Hive

AWS

Git

CI/CD

Airflow

Job description

Akaasa Technologies is seeking a Senior Data Engineer to design, develop, and optimize scalable data platforms powering analytics, ML, and AI-driven solutions. You will work with Databricks, Spark, Delta Lake, Snowflake, Kafka, and AWS, contributing to GenAI, LLMs, RAG, and AI-assisted engineering.

The role emphasizes data quality, governance, and enterprise-scale data engineering across batch and streaming pipelines, with cloud-native, cost-efficient architectures.