Senior Data Engineer

SAKSOFT PTE LIMITED; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

SAKSOFT PTE LIMITED is seeking a Senior Data Engineer with 10+ years of experience to design and operate enterprise Lakehouse platforms and data products. You will build scalable batch and streaming pipelines, support RAG, vector search, GenAI and deploy data contracts and governance.

You will collaborate across teams to implement open table formats like Iceberg, Hudi, Delta Lake, manage metadata, and expose data via APIs and BI tools, while ensuring performance and security in a cloud-native

Qualifications

• Bachelor’s degree in Computer Science, Engineering or related discipline.
• 10+ years in data engineering, big data, data lake or lakehouse implementations.

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.

Skills

Spark

PySpark

SQL

Python

Java

Scala

Data Modeling

Metadata Management

Governance

APIs

BI Dashboards

CI/CD

Kubernetes

OpenShift

Docker

Airflow

Kafka

Flink

Spark Streaming

MLflow

Terraform

Jenkins

Git

Scikit-learn

XGBoost

Education

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

Tools

Databricks

Snowflake

Cloudera

Azure

AWS

GCP

Huawei

Alibaba

Iceberg

Hudi

Delta Lake

Trino

Dremio

Hive

Impala

Kafka

Flink

Spark Streaming

Airflow

Kubernetes

OpenShift

Docker

CI/CD

MLflow

Terraform

Jenkins

Git

CML

Spark MLlib

scikit-learn

XGBoost

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.