Senior Data Engineer

Saksoft Pte Ltd; Singapore; On-site; SGD 120,000 - 160,000; Full time

Benefits offered by this job

Databricks Certified Data Engineer

Job summary

Saksoft Pte Ltd is seeking a Senior Data Engineer in Singapore to design and operationalize lakehouse platforms, data products, and data marketplace capabilities. You will develop scalable batch and streaming pipelines, enabling NLP/AI analytics and govern unstructured data within data lakes and warehouses.

You’ll work with modern data stacks, data governance, and open formats like Iceberg/Hudi/Delta Lake, while collaborating across distributed teams to ensure performance and reliability.

Qualifications

• Bachelor’s degree in Computer Science, Engineering or related discipline

Responsibilities

• Implement and operationalize enterprise Lakehouse platforms, data products, and data marketplace capabilities.

Skills

Spark

PySpark

SQL

Python

Java

Scala

Data ingestion

Data governance

APIs

Data modelling

Data quality

Spark Streaming

NLP/AI analytics

Education

Bachelor’s degree in Computer Science

Databricks Certified Data Engineer

Azure Data Engineer Associate

AWS Data Analytics Specialty

Google Professional Data Engineer

SnowPro Certification

DAMA CDMP

Tools

Databricks

Snowflake

Cloudera

Azure

AWS

GCP

Huawei

Alibaba

Kubernetes

OpenShift

Docker

CI/CD

MLflow

Airflow

Kafka

Spark

PySpark

Iceberg

Hudi

Delta Lake

Job description

Experience: 10+ Years
Role: Senior Data Engineer

Key Skills:

• 8-12 years of experience in Data Engineering, Big Data, Data Lake, or Lakehouse implementations.
• Hands-on experience with Databricks, Snowflake, Cloudera, Azure, AWS, GCP, Huawei, or Alibaba data platforms.
• Hands-on experience in developing Data products and Market place
• Strong expertise in Spark, PySpark, SQL, Python and Scala.
• Strong programing skills (Java, Scala, Python, SQL)
• Experience with Iceberg, Hudi, Delta Lake and object storage platforms.
• Experience implementing data ingestion, transformation, reconciliation and data quality frameworks.
• Experience with Trino, Dremio, Hive, Impala, Kafka, Flink, Spark Streaming and Airflow.
• Strong hands on experience with Kubernetes, OpenShift, Docker, CI/CD, MLflow and observability tools.
• Ability to design data architectures supporting NLP and AI‑driven analytics, including ingestion, curation, and governance of unstructured data within Data Lake, Data warehouse platforms.
• Experience working with ML platforms such as CML, Spark MLlib, and Python ML libraries (scikit‑learn, XGBoost), including model deployment.
• Develop full‑stack applications and internal engineering tools using Python, shell scripting, and modern web frameworks (e.g., Flask, React).
• Knowledge of data modelling, metadata management, lineage and governance.
• Experience exposing data through APIs, event streams, dashboards and BI platforms.
• Knowledge of Teradata, Netezza, Greenplum or MPP migration programs is advantageous.
• Experience with Kubernetes, OpenShift, Terraform, Jenkins, Git and CI/CD pipelines.

Responsibilities:

• Implement and operationalize enterprise Lakehouse platforms, data products, and data marketplace capabilities.
• Develop scalable batch, streaming, CDC, and API-based data ingestion pipelines.
• Develop scalable multimodal data ingestion pipelines including content extraction from various file formats, regex for specific field extraction, content extraction from embedded images, frame extraction from video files, transcript extraction from audio files, etc
• Build, test, and maintain foundation and business data products with agreed data contracts, SLAs, and data quality controls.
• Implement open table formats such as Iceberg, Hudi, and Delta Lake.
• Support RAG, vector search, GenAI and agentic data pipelines.
• Perform performance tuning, optimization, production support, and root cause analysis.
• Create technical documentation, deployment guides, and operational runbooks.
• Ensure compliance with engineering standards, DevSecOps controls, and software delivery practices.

Requirements:

EDUCATION

• Bachelor’s degree in Computer Science, Engineering or related discipline

PREFERRED CERTIFICATIONS

• Databricks Certified Data Engineer
• Azure Data Engineer Associate
• AWS Data Analytics Specialty
• Google Professional Data Engineer
• SnowPro Certification
• DAMA CDMP
• Strong engineering and automation mindset.
• Excellent troubleshooting and performance optimization skills.
• Ability to work across distributed teams and multiple projects.
• Strong communication and stakeholder management skills.
• Experience in Agile delivery and enterprise-scale platforms.
• Commitment to quality, operational excellence and continuous improvement.