Sr Data Engineer - Data Bricks / MS Fabric Anblicks

  • company name Anblicks
  • working location Office Location
  • job type Full Time

Experience: 4 - 4 years required

Pay:

Salary Information not included

Type: Full Time

Location: Hyderabad

Skills: Python, SQL, pyspark, Data Bricks, MS Fabric

About Anblicks

Job Description

Role: Senior Data Engineer Location: Hyderabad or Ahmedabad Experience: 5+ Years Skill: Python, PySpark, SQL & Data Bricks / MS Fabric Preferred Immediate to 30 days joiners. About the Role: We are seeking an experienced Senior Data Engineer to join our team. This role requires expertise in designing, developing, and optimizing high-performance data pipelines while leveraging cloud platforms and distributed data processing frameworks. As a key member of our data engineering team, you will play a pivotal role in data architecture, modeling, governance, and automation, ensuring efficiency, scalability, and security across our data ecosystems. Additionally, you will mentor junior engineers and drive best practices in data engineering. Key Responsibilities Design and develop high-performance, scalable data pipelines using PySpark, SQL, and cloud platforms. Optimize distributed data processing for improved efficiency and reliability. Implement best practices in data modeling, architecture, and governance. Ensure data integrity, security, and compliance within cloud environments. Automate data workflows, monitor pipeline performance, and troubleshoot issues proactively. Provide technical leadership and mentorship to junior engineers, conduct code reviews, and establish best practices. Required Skills & Experience 4+ years of hands-on experience in Data Engineering with expertise in Python, PySpark,Spark, SQL, and Cloud platforms. Strong proficiency in Databricks, or Microsoft Fabric. Solid experience in data architecture, modeling, and pipeline optimization. Hands-on experience with workflow orchestration tools (e.g., Airflow, DBT). Proven ability to mentor and lead junior engineers while driving best practices in data engineering.,