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ProAnalyst

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Senior Data Engineer

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Summary

Senior Data Engineer (6–8 yrs) at ProAnalyst, a data & AI consulting firm in Bangalore (hybrid, 3 days WFO). Day to day: design and maintain scalable ETL/ELT pipelines, write and optimize complex SQL, build Python data-processing solutions, and work with cloud data platforms (GCP preferred) for global clients.

Location: ARK Tech Park, HSR Layout, Bangalore (Hybrid – 3 Days WFO)

Company: ProAnalyst – Data & AI Services

Experience: 6 - 8 Years

Range: Upto 12LPA

Type: Full-time

Reporting To: Founder & Lead Consultant


About ProAnalyst


ProAnalyst is a data analytics & BI consulting firm. We deliver dashboards, data pipelines, and analytics teams for clients across the US, Australia, and India, with a growing AI service line. We’re expanding our Data Engineering capabilities, and this role offers the opportunity to work on high-impact data and analytics projects for global clients.


Role Overview


We are looking for an experienced Data Engineer with 6–8 years of hands-on experience in designing, developing, and maintaining scalable data pipelines and data processing solutions.


The ideal candidate should have strong expertise in SQL and Python, practical experience working with cloud-based data platforms, and a solid understanding of data engineering, ETL/ELT, data transformation, data quality, and pipeline optimization.


Experience with Google Cloud Platform (GCP) is strongly preferred, particularly candidates who have worked with cloud-based data warehousing and data processing environments.

The candidate should be technically strong, detail-oriented, capable of independently troubleshooting data issues, and confident in communicating with technical and business stakeholders.


Key Responsibilities


  • Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
  • Write, optimize, and troubleshoot complex SQL queries across large datasets.
  • Develop Python-based solutions for data processing, automation, and transformation.
  • Work with cloud-based data platforms and data warehouses.
  • Build and maintain reliable data ingestion and transformation workflows.
  • Perform data validation, quality checks, reconciliation, and troubleshooting.
  • Identify and resolve pipeline, data quality, and performance issues.
  • Optimize data processing workflows for scalability and efficiency.
  • Collaborate with data analysts, BI developers, engineers, and business stakeholders.
  • Translate business and technical requirements into reliable data engineering solutions.
  • Document data pipelines, processes, and technical solutions.


Ideal Candidate


  • 6–8 years of experience in Data Engineering or related roles.
  • Strong hands-on expertise in SQL and Python.
  • Strong understanding of ETL/ELT, data pipelines, data transformation, and data integration.
  • Hands-on experience with cloud data platforms; GCP is preferred.
  • Experience working with large datasets and cloud data warehouses.
  • Strong understanding of data quality, validation, and performance optimization.
  • Strong problem-solving and analytical skills.
  • Good communication and stakeholder-management skills.
  • Ability to work independently and take ownership of technical deliverables.
  • Databricks and Airflow experience is a plus.


Knowledge Requirement


Data Engineering & ETL/ELT – 40%

SQL & Python – 30%

Cloud & Data Platforms – 20%

Problem Solving & Communication – 10%


Interview Process


  • Round 1: AI Video InterviewCommunication, technical knowledge, leadership mindset, and problem-solving.
  • Round 2: Technical Interview – BI, SQL & Data EngineeringSQL, Power BI, data modeling, data engineering, visualization, and technical problem-solving.
  • Round 3: Founder’s Round Leadership, ownership, client handling, team management, problem-solving approach, and overall suitability


Why Join Us?


  • Work on real-world Data, AI, and Analytics projects.
  • Exposure to modern cloud and data engineering technologies.
  • Opportunity to work with global clients and diverse data problems.
  • High ownership and direct exposure to experienced technical leadership.
  • Opportunity to grow within a fast-growing Data & AI consulting firm.

Skills

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