Senior Data Engineer

About The Role

Data Engineer

Key Responsibilities

• Design, develop, and maintain

  ETL/ELT pipelines

  using Databricks, Fabric, or Snowflake.
• Build and optimize

  data workflows

  for performance, scalability, and cost efficiency in cloud environments (Azure/AWS/GCP).
• Implement and manage

  data lakes, data warehouses, or lakehouse architectures

  .
• Develop and maintain

  Power BI dashboards and reports

  to support business insights and decision-making.
• Collaborate with cross-functional teams to define

  data requirements, governance standards, and best practices

  .
• Ensure

  data quality, integrity, and security

  across all platforms.
• Automate workflows and support

  CI/CD deployments

  for data solutions.
• Monitor and troubleshoot pipelines and dashboards to ensure high availability and reliability.

Required Qualifications

• Bachelor's/Master's degree

  in Computer Science, Information Technology, Engineering, or related field.

• 5-7 years

  of experience in Data Engineering.
• Proven experience as a

  Data Engineer

  with expertise in

  Databricks OR Fabric OR Snowflake

  .
• Hands-on experience with

  Power BI

  (data modeling, DAX, dashboard creation, performance optimization).
• Strong proficiency in

  SQL

  and at least one programming language (Python/Scala/Java).
• Experience with

  data modeling

  and building scalable pipelines in cloud environments.
• Knowledge of

  Azure, AWS, or GCP

  and their data ecosystem.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with

  streaming data technologies

  (Kafka, Event Hubs, Kinesis).
• Knowledge of

  Delta Lake, Synapse, or Snowflake performance optimization

  .
• Familiarity with

  DevOps practices

  for data (CI/CD, Git, Infrastructure as Code).
• Exposure to

  machine learning pipelines

  or advanced analytics.
• Understanding of

  data governance, lineage, and compliance frameworks