Senior Data Engineer

10 people have applied

Mirpur, Dhaka · onsite · full time

Workplace address: Mirpur 10, Dhaka, Dhaka, 1216, BD

BDT 100,000 – 180,000 / month

Hiring now

1

Planned later

0

About the role

Lead hands-on data engineering at a confidential partner company across company products and client engagements. Build dependable data platforms and support analytics and applied machine learning while mentoring three Data Engineering Interns. Assignments may vary with business needs. Responsibilities - Translate business needs into data architectures, ingestion pipelines and clear data contracts. - Build reliable batch and streaming workflows with validation, deduplication, monitoring and recovery. - Design traceable storage for raw data, curated datasets, features and model artifacts. - Support reproducible model training and evaluation, with versioned datasets, experiments and deployment processes. - Work with software engineers to integrate data services, analytics and model outputs through secure APIs. - Maintain data access controls, documentation and performance standards. - Mentor data interns through reviewed tasks and communicate technical trade-offs and limitations clearly. Early success Establish a reliable, documented data workflow with quality checks and a repeatable approach to analytics or model development. Current openings: 1. How to apply Apply through this ALHarih job page with your CV and a short note describing relevant work. A dataset-cleaning, SQL or pipeline example with checks for missing data, duplicates and reproducibility. Share only material you have permission to disclose, and explain your own contribution. You can build a CV at https://alharih.com/resume-builder. Selection process Applications are reviewed against the published requirements. If invited, follow the role-specific assessment instructions in your ALHarih account. An invitation or completed assessment is not a job offer.

Requirements

- Strong production data-engineering experience with Python, SQL, data modelling and ingestion pipelines. - Experience diagnosing data-quality problems and operating reliable data services. - Practical applied machine-learning knowledge, including feature preparation, evaluation, leakage prevention and reproducible training. - Experience versioning datasets and model artifacts, with monitoring, access controls and recovery procedures. - Ability to lead technical decisions, collaborate across functions and mentor junior colleagues. - Experience with time-series data, event streams or cloud data platforms is a useful advantage. - Ability to explain data lineage and validate results using repeatable checks appropriate to your experience level.