Data & AI Engineer

2 days ago


Dhaka, Dhaka, Bangladesh Epic Group Full time ৳1,200,000 - ৳2,400,000 per year

We are seeking a technically strong and business-savvy Data & AI Engineer to drive enterprise-wide data and AI transformation initiatives. This role will focus on building scalable data pipelines, implementing robust data quality frameworks, and enabling intelligent analytics and automation across business functions.

Key Responsibilities:

  • Design, build, and maintain scalable and secure data pipelines across cloud and on-prem environments.
  • Integrate data from ERP (e.g., SAP), BI platforms (e.g., SAC), and external sources into centralized data lakes or warehouses.
  • Optimize ETL/ELT processes for performance, reliability, and cost-efficiency.
  • Define and implement data quality rules, validation checks, and cleansing routines.
  • Collaborate with business and IT teams to ensure data accuracy, consistency, and completeness.
  • Monitor data lineage and metadata to support compliance and audit readiness.
  • Partner with data scientists and analysts to operationalize AI/ML models.
  • Support use cases such as forecasting, anomaly detection, and intelligent automation (e.g., RPA, OCR).
  • Enable self-service analytics and reporting through platforms like Power BI, SAC, or Tableau.
  • Work closely with cross-functional teams including IT, business improvement, and factory operations.
  • Mentor junior engineers and analysts, fostering a culture of innovation and continuous learning.
  • Act as a bridge between technical teams and business stakeholders to translate requirements into scalable solutions.

Qualifications, experience and skills required:

  • Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
  • Minimum 5-6 years of experience in data engineering, analytics, or AI/ML implementation.
  • Strong proficiency in SQL, Python, Spark, and cloud platforms (Azure, AWS, GCP).
  • Experience with data quality tools, governance frameworks, and metadata management.
  • Familiarity with AI/ML lifecycle, model deployment, and MLOps practices.
  • Excellent communication, problem-solving, and stakeholder management skills.


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