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Data Engineer

Data Engineer

HORIZON COMPUTER MANAGEMENT PTE. LTD.Singapore, Singapore, Singapore
18 days ago
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

    #J-18808-Ljbffr

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    Data Engineer • Singapore, Singapore, Singapore

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