Data Engineer (AWS + Databricks + IDMC)

EVYONIC SOLUTIONS PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading tech solutions provider in Singapore is seeking a seasoned Data Engineer. You will design and optimize data storage solutions using AWS, Databricks, and Informatica IDMC. The ideal candidate will have at least 7 years of experience, a strong background in programming languages like Python or Java, and profound knowledge of SQL and NoSQL technologies. This role promotes a collaborative atmosphere, requiring excellent communication skills and a passion for data engineering best practices.

Qualifications

• Minimum 7 years of experience in data engineering.
• Proficiency in Python, Java, or Scala for building data pipelines.
• Strong knowledge of both SQL and NoSQL databases.
• Experience with big data technologies like Apache Spark and Hadoop.
• Familiarity with data governance tools, especially Informatica IDMC.

Responsibilities

• Design and architect data storage solutions using AWS services.
• Optimize data pipelines for ingesting and transforming data.
• Monitor and optimize data processing and query performance.
• Implement security best practices to protect sensitive data.
• Collaborate with cross-functional teams to deliver data solutions.

Skills

AWS services

Databricks

Informatica IDMC

Python

Java

Scala

SQL

NoSQL databases

Apache Spark

Hadoop

Education

Bachelor’s or master’s degree in computer science, data engineering, or a related field

Tools

Docker

Kubernetes

Tableau

Power BI

Job description

Responsibilities

• Design and architect data storage solutions, including databases, data lakes, and warehouses, using AWS services such as Amazon S3, Amazon RDS, Amazon Redshift, and Amazon DynamoDB, along with Databricks' Delta Lake. Integrate Informatica IDMC for metadata management and data cataloging.
• Create, manage, and optimize data pipelines for ingesting, processing, and transforming data using AWS services like AWS Glue, AWS Data Pipeline, and AWS Lambda, Databricks for advanced data processing, and Informatica IDMC for data integration and quality.
• Integrate data from various sources, both internal and external, into AWS and Databricks environments, ensuring data consistency and quality, while leveraging Informatica IDMC for data integration, transformation, and governance.
• Develop ETL (Extract, Transform, Load) processes to cleanse, transform, and enrich data, making it suitable for analytical purposes using Databricks' Spark capabilities and Informatica IDMC for data transformation and quality.
• Monitor and optimize data processing and query performance in both AWS and Databricks environments, making necessary adjustments to meet performance and scalability requirements. Utilize Informatica IDMC for optimizing data workflows.
• Implement security best practices and data encryption methods to protect sensitive data in both AWS and Databricks, while ensuring compliance with data privacy regulations. Employ Informatica IDMC for data governance and compliance.
• Implement automation for routine tasks, such as data ingestion, transformation, and monitoring, using AWS services like AWS Step Functions, AWS Lambda, Databricks Jobs, and Informatica IDMC for workflow automation.
• Maintain clear and comprehensive documentation of data infrastructure, pipelines, and configurations in both AWS and Databricks environments, with metadata management facilitated by Informatica IDMC.
• Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and deliver appropriate solutions across AWS, Databricks, and Informatica IDMC.
• Identify and resolve data-related issues and provide support to ensure data availability and integrity in both AWS, Databricks, and Informatica IDMC environments.
• Optimize AWS, Databricks, and Informatica resource usage to control costs while meeting performance and scalability requirements.
• Stay up-to-date with AWS, Databricks, Informatica IDMC services, and data engineering best practices to recommend and implement new technologies and techniques.

Requirements

• Bachelor’s or master’s degree in computer science, data engineering, or a related field.
• Minimum 7 years of experience in data engineering, with expertise in AWS services, Databricks, and/or Informatica IDMC.
• Proficiency in programming languages such as Python, Java, or Scala for building data pipelines.
• Evaluate potential technical solutions and make recommendations to resolve data issues especially on performance assessment for complex data transformations and long running data processes.
• Strong knowledge of SQL and NoSQL databases.
• Familiarity with data modeling and schema design.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.
• AWS certifications (e.g., AWS Certified Data Analytics - Specialty, AWS Certified Data Analytics - Specialty), Databricks certifications, and Informatica certifications are a plus.
• Experience with big data technologies like Apache Spark and Hadoop on Databricks.
• Knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Familiarity with data visualization tools like Tableau or Power BI.
• Understanding of DevOps principles for managing and deploying data pipelines.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Knowledge of data governance and data cataloguing tools, especially Informatica IDMC.