Job title: Senior Data Engineer

Job Description

Senior Data Engineer

About the Company

Our client is a fast-growing Singapore-based Data Science & AI consultancy that helps organizations transform data into actionable insights and intelligent business decisions. The company specializes in building enterprise data platforms, AI-powered analytics, machine learning solutions, and automation systems that enable businesses to scale with confidence. Backed by a collaborative and innovation-driven culture, they work with modern cloud technologies and deliver end-to-end data and AI solutions across a wide range of industries.

 

Overview

As a Senior Data Engineer, you will design, build, and optimize scalable data pipelines and platforms that power analytics, dashboards, and AI solutions across the enterprise. You will ensure data is reliable, accessible, and production-ready while driving automation, scalability, and engineering best practices.

Key Responsibilities

1. Data Pipeline Development

  • Design, build, and maintain scalable data pipelines for data ingestion, transformation, and delivery.
  • Automate ETL/ELT workflows using tools such as Airflow, Glue, Step Functions, or Prefect.
  • Implement data validation, version control, and rollback mechanisms.
  • Build resilient, self-healing pipelines with minimal downtime.

2. Data Platform & Infrastructure

  • Develop and optimize data lakehouse and warehouse solutions using Databricks, Snowflake, Redshift, S3, EMR, Glue, and Lake Formation.
  • Improve query performance through partitioning, indexing, and caching.
  • Implement monitoring, logging, and alerting using CloudWatch, Prometheus, or Grafana.
  • Work with the Data Architect to ensure scalable and efficient data platforms.

3. AI & Analytics Support

  • Build data pipelines supporting AI models and business analytics.
  • Work with Data Scientists to develop model deployment and retraining pipelines.
  • Develop reusable feature stores, model registries, and MLOps frameworks.
  • Support AI-powered analytics and LLM integration.

4. Data Quality & Governance

  • Maintain documentation for data pipelines, lineage, and metadata.
  • Ensure compliance with data governance, security, PDPA, and GDPR requirements.
  • Implement automated data quality checks, anomaly detection, and audit trails.
  • Deliver clean, reliable, and production-ready data.

5. Business Collaboration

  • Partner with Product, Engineering, and Data Science teams to deliver data solutions.
  • Build reusable datasets for business reporting and analytics.
  • Translate business and AI requirements into scalable data engineering solutions.

6. Continuous Improvement

  • Implement CI/CD pipelines, Infrastructure-as-Code, and containerized ETL processes.
  • Evaluate new technologies to improve automation and performance.
  • Promote reusable, maintainable, and scalable engineering practices.

Qualifications

Education

  • Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.

Experience

  • 6+ years of experience in data engineering, data platforms, or infrastructure.
  • Experience managing large-scale datasets and production data pipelines.

Technical Skills

  • Strong SQL and Python programming skills.
  • Experience with Spark, Hadoop, dbt, and Airflow.
  • Strong knowledge of AWS services including Redshift, Glue, S3, EMR, Athena, Lambda, and Lake Formation.
  • Experience with Databricks, Snowflake, SageMaker, MLflow, or Vertex AI.
  • Knowledge of data modelling, performance tuning, cost optimization, and data governance.

Preferred

  • AWS Certified Data Engineer, AWS Solutions Architect, or equivalent certification.

 

Interested candidates may click on apply or apply via email to kenwi.g@scientecconsulting.com

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Kenwi Goh Jian Wee – R26159880
ScienTec Consulting Pte Ltd - 11C5781