Data Engineer

ACCORD INNOVATIONS PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

ACCORD INNOVATIONS PTE. LTD.

in Singapore is seeking an experienced Data Engineer to design, build and optimise scalable data pipelines and analytics infrastructure, spanning ingestion, transformation, modelling and delivery of high-performance datasets for business intelligence. The role requires hands-on expertise with Snowflake, Python and ETL/ELT, plus exposure to real-time analytics platforms such as Apache Doris; you will collaborate with analysts, data scientists and BI teams to translate

Qualifications

• At least 5 years of experience in Data Engineering or a closely related role.
• Strong hands-on Snowflake experience including SQL, Snowpipe, Streams/Tasks and performance tuning.
• Solid SQL and data-modelling skills with dimensional modeling and star/snowflake schemas.
• Proficiency in Python for data engineering and automation.
• Experience with ETL/ELT development and data pipeline engineering.
• Experience with workflow orchestration tools such as Apache Airflow, dbt, Dagster or similar.
• Understanding of streaming/messaging tech like Kafka, Pulsar or similar.
• Good knowledge of data warehousing concepts and distributed systems.
• Experience with Git and CI/CD practices for data projects.

Responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines for structured and semi-structured data.
• Build data pipelines integrating multiple sources with Snowflake and analytical platforms.
• Develop and optimise data models, schemas and partitioning for analytical workloads.
• Perform SQL query optimisation and data warehouse performance tuning.
• Manage Snowflake warehouses, including sizing, resource utilisation, monitoring and cost control.
• Develop and maintain workflow orchestration using Airflow, dbt, Dagster or similar.
• Implement data quality checks, validation and pipeline monitoring.
• Support data integration and migration across transactional systems, data lakes and cloud warehouses.
• Collaborate with data analysts, data scientists and BI teams to translate requirements into scalable data solutions.
• Implement data governance, security and access-control practices, including RBAC and data protection.
• Maintain technical documentation covering data architecture, pipeline logic and operational procedures.

Skills

Snowflake

Python

ETL/ELT

SQL

Data modelling

Airflow

dbt

Dagster

Kafka

Kubernetes

Git

CI/CD

AWS

Azure

GCP

Power BI

Tableau

Tools

Snowflake

Apache Airflow

dbt

Dagster

Kafka

Pulsar

Git

Kubernetes

Power BI

Tableau

Looker

Superset

AWS

Azure

GCP

Terraform

Job description

Job Description

About the Role

We are seeking an experienced Data Engineer to design, develop and optimize scalable data pipelines and analytics infrastructure. The successful candidate will work across the full data lifecycle, including data ingestion, transformation, modelling and delivery of high-performance analytical datasets.

The role requires strong hands‑on experience in Snowflake, Python and ETL/ELT, with exposure to real‑time analytical platforms such as Apache Doris.

Key Responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines for structured and semi‑structured data.
• Build data pipelines integrating multiple data sources with Snowflake and analytical platforms.
• Develop and optimize data models, schemas and partitioning strategies for analytical workloads.
• Perform SQL query optimization and data warehouse performance tuning.
• Manage Snowflake warehouses, including sizing, resource utilisation, monitoring and cost optimisation.
• Develop and maintain workflow orchestration using tools such as Airflow, dbt, Dagster or similar.
• Implement data quality checks, validation and pipeline monitoring.
• Support data integration and migration initiatives involving transactional systems, data lakes and cloud data warehouses.
• Collaborate with data analysts, data scientists and BI teams to translate business requirements into scalable data solutions.
• Implement data governance, security and access‑control practices, including RBAC and data protection.
• Maintain technical documentation covering data architecture, pipeline logic and operational procedures.

Requirements

• At least 5 years of relevant experience in Data Engineering or a closely related role.
• Strong hands‑on experience with Snowflake, including SQL, warehouse management, Snowpipe, Streams/Tasks and performance optimisation.
• Strong SQL and data‑modelling skills, including dimensional modelling and star/snowflake schemas.
• Proficiency in Python for data engineering and automation.
• Experience with ETL/ELT development and data pipeline engineering.
• Experience with workflow orchestration tools such as Apache Airflow, dbt, Dagster or similar.
• Understanding of streaming and messaging technologies such as Kafka, Pulsar or similar.
• Good understanding of data warehousing, OLAP/OLTP concepts and distributed systems.
• Experience using Git and CI/CD practices for data engineering projects.

Preferred Skills

• Experience migrating traditional data warehouse workloads to Snowflake or Apache Doris.
• Experience with AWS, Azure or GCP.
• Experience with Docker and Kubernetes.
• Familiarity with Terraform, CloudFormation or similar infrastructure‑as‑code tools.
• Experience with BI tools such as Power BI, Tableau, Looker or Superset.
• Experience in analytical platform cost optimisation and capacity planning.

Top 3 Skills

1. Snowflake
2. Python
3. ETL / ELT

Additional Technical Skills

SQL | Apache Airflow | dbt | Kafka | Apache Doris | Data Modelling | Git | CI/CD | AWS/Azure/GCP | Kubernetes | Power BI/Tableau