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Urgent! Data Engineer Job Opening In Singapore, Singapore – Now Hiring HORIZON COMPUTER MANAGEMENT PTE. LTD.



Job description

Key Responsibilities

  • Design, build, and maintain robust, scalable, and secure data pipelines for batch and real-time data processing.

  • Develop and optimize ETL/ELT workflows to extract, transform, and load data from multiple sources.

  • Architect and implement data warehouses, data lakes, and lakehouse solutions on cloud or on-prem platforms.

  • Ensure data quality, lineage, governance, and versioning using metadata management tools.

  • Collaborate with Data Scientists, Analysts, and Software Engineers to deliver reliable and accessible data solutions.

  • Optimize SQL queries, data models, and storage layers for performance and cost efficiency.

  • Develop and maintain automation scripts for data ingestion, transformation, and orchestration.

  • Integrate and process large-scale data from APIs, flat files, streaming services, and legacy systems.

  • Implement data security, access control, and compliance standards (GDPR, ISO 27001) .

  • Monitor and troubleshoot data pipeline failures, latency, and performance bottlenecks .

Data Engineering & Architecture

  • Strong expertise in data modeling (dimensional/star/snowflake schemas) and data normalization techniques .

  • Proficient in ETL/ELT tools such as Apache NiFi, Talend, Informatica, SSIS, or Airbyte .

  • Advanced knowledge of SQL and distributed computing concepts .

  • Experience with data lake and warehouse technologies such as Snowflake, Redshift, BigQuery, Azure Synapse, or Databricks .

  • Deep understanding of data partitioning, indexing, and query optimization .

Big Data & Distributed Systems

  • Hands-on experience with Hadoop ecosystem (HDFS, Hive, HBase, Oozie, Sqoop) .

  • Proficiency in Apache Spark / PySpark for distributed data processing.

  • Exposure to streaming frameworks like Kafka, Flink, or Kinesis .

  • Familiarity with NoSQL databases such as MongoDB, Cassandra, or Elasticsearch .

  • Knowledge of data versioning and catalog systems (e.g., Delta Lake, Apache Hudi, Iceberg, or AWS Glue Data Catalog).

Programming & Automation

  • Strong programming skills in Python , Scala , or Java for data manipulation and ETL automation.

  • Experience with API integration, REST/GraphQL, and data serialization formats (JSON, Parquet, Avro, ORC).

  • Proficient in shell scripting, automation, and orchestration tools (Apache Airflow, Prefect, or Luigi).

Cloud Platforms

  • Expertise in at least one cloud ecosystem:
    AWS: S3, Redshift, Glue, EMR, Lambda, Athena, Kinesis
    Azure: Data Factory, Synapse, Blob Storage, Databricks
    GCP: BigQuery, Dataflow, Pub/Sub, Cloud Composer
  • Strong understanding of IAM, VPC, encryption, and data access policies within cloud environments.

Data Governance & Security

  • Implement and enforce data quality frameworks (DQ checks, profiling, validation rules) .

  • Knowledge of metadata management, lineage tracking , and master data management (MDM) .

  • Familiarity with role-based access control (RBAC) and data encryption mechanisms.

Preferred Skills

  • Experience with machine learning data pipelines (ML Ops) or feature store management .

  • Knowledge of containerization and orchestration tools (Docker, Kubernetes).

  • Familiarity with CI/CD pipelines for data deployment.

  • Exposure to business intelligence (BI) tools like Power BI, Tableau, or Looker for data delivery.

  • Understanding of data mesh or domain-driven data architecture principles .

Leadership & Collaboration

  • Work closely with cross-functional teams to define data requirements and best practices.

  • Mentor junior engineers and enforce coding and documentation standards .

  • Provide technical input in data strategy, architecture reviews, and technology evaluations .

  • Collaborate with security and compliance teams to ensure data integrity and protection.

Qualifications

  • Bachelor’s or Master’s Degree in Computer Science, Data Engineering, Information Systems, or related field.

  • 5–10 years of professional experience as a Data Engineer or similar role.

  • Professional Certifications preferred:
    AWS Certified Data Analytics / Big Data Specialty
    Microsoft Certified: Azure Data Engineer Associate
    Google Professional Data Engineer
    Databricks Certified Data Engineer

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Required Skill Profession

Database, Analytics & Bi



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