Data Engineer -Snowflake

Skills : Snowflake + DBT + Iceberg + Apacheflink

Exp: 5 to 10 years

NP: Immediate to 15 Days

Location: Hyderabad

About the Role

Data Engineer

You will work closely with data analysts, data scientists, and platform engineers to ensure efficient, scalable, and reliable data workflows across the organization.

Key Responsibilities

• Design, develop, and maintain

  data pipelines

  and

  data models

  using

  Snowflake

  and

  DBT

  .
• Implement

  data transformations

  ,

  data validation

  , and

  metadata management

  using modern ELT frameworks.
• Build and manage

  real-time data processing

  systems using

  Apache Flink

  (or similar stream-processing technologies).
• Integrate batch and streaming data into

  data lakehouse environments

  (Iceberg, Delta Lake, or similar).
• Optimize Snowflake performance through

  query tuning

  ,

  clustering

  , and

  data partitioning strategies

  .
• Collaborate with cross-functional teams to understand business data needs and translate them into scalable solutions.
• Ensure

  data quality, security, and governance

  best practices are followed throughout the pipeline lifecycle.
• Support CI/CD automation for DBT and data infrastructure deployments.
• Monitor, troubleshoot, and enhance data systems for performance and reliability.

Required Qualifications

• 3–6 years

  of experience in

  Data Engineering

  or

  Analytics Engineering

  roles.
• Strong expertise in

  Snowflake

  (data modeling, performance tuning, security, cost optimization).
• Hands-on experience with

  DBT (Data Build Tool)

  — building modular, testable, and documented data models.
• Proficiency in

  SQL

  and one programming language (e.g., Python, Java, or Scala).
• Working knowledge of

  Apache Flink

  or other streaming frameworks (Kafka Streams, Spark Structured Streaming).
• Experience with

  Apache Iceberg

  ,

  Delta Lake

  , or similar lakehouse formats.
• Familiarity with

  cloud platforms

  (AWS, GCP, or Azure) and modern data orchestration tools (Airflow, Dagster, Prefect).
• Strong understanding of

  data warehousing concepts

  ,

  ETL/ELT

  , and

  data governance

  .

Preferred Qualifications

• Experience integrating Snowflake with

  streaming and lakehouse architectures

  .
• Knowledge of

  modern data stack

  tools (Fivetran, Airbyte, Great Expectations, etc.).
• Exposure to

  DevOps

  or

  DataOps

  principles (CI/CD, Git, Infrastructure as Code).
• Background in

  real-time analytics

  ,

  event-driven architectures

  , or

  ML feature pipelines

  .

Soft Skills

• Excellent problem-solving and analytical thinking.
• Strong communication and collaboration across technical and non-technical teams.
• Ownership mindset and ability to work independently in a fast-paced environment.

Education

• Bachelor’s or master’s degree in computer science,

  Data Engineering

  ,

  Information Systems

  , or a related field (or equivalent experience).