Senior Data Engineer – Engineering

Deloitte

Data Engineer designing, developing, and deploying scalable data solutions at Deloitte. Collaborating with cross-functional teams to improve data processes and support applications.

Posted 8/3/2026full-timeSingapore • 🇸🇬 SingaporeSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing data pipelines, data warehouses, and backend APIs while ensuring data accuracy and compliance. Proficient in cloud technologies and big data frameworks, with a strong focus on data engineering best practices.

Highest-signal resume keywords

Data Pipeline DevelopmentETL Pipeline BuildingDatabase DesignCloud Technologies ExperienceData Governance Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData CleaningData TransformationETLAWSPostgreSQLHadoopSparkData Modeling

Soft Skills

CollaborationAgile MethodologyPair Programming

Tools & Technologies

AWS LambdaSQL Server Integration ServicesAWS GlueEventbridgeMongoDBRabbitMQBeautifulSoupSeleniumLinuxWindows

Industry Keywords

Data WarehouseData LakeData VirtualizationBig DataData Governance

Tech Stack

Tools & technologies

AWSAzureCassandraCloudETLHadoopKafkaLinuxMongoDBMySQLNode.jsPandasPostgresPythonRabbitMQSeleniumSparkSpringSQLSQLiteSSIS

About the role

Key responsibilities & impact

Design, develop and deploy data tables, views and marts in data warehouses, operational data store, data lake and data virtualization
Perform data extraction, cleaning, transformation, and flow
Design, build, launch and maintain efficient and reliable large-scale batch and real-time data pipelines with data processing frameworks
Integrate and collate data silos in a manner which is both scalable and compliant
Collaborate with Project Manager, Data Architect, Business Analysts, Frontend Developers, Designers and Data Analyst to build scalable data-driven products
Be responsible for developing backend APIs & working on databases to support the applications
Work in an Agile Environment that practices Continuous Integration and Delivery
Work closely with fellow developers through pair programming and code review process

Requirements

What you’ll need

2-3 years of relevant working experience as a data engineer
Proficient in general data cleaning and transformation (e.g. SQL, pandas, R, etc) to ensure data accuracy and consistency
Proficient in building ETL pipeline (eg. SQL Server Integration Services (SSIS), AWS Database Migration Services (DMS), Python, AWS Lambda, ECS Container task, Eventbridge, AWS Glue, Spring)
Proficient in database design and various databases (e.g. SQL, PostgreSQL, AWS S3, Athena, mongodb, postgres/gis, mysql, sqlite, voltdb, cassandra, etc)
Experience in cloud technologies such as GPC, GCC (i.e. AWS, Azure, Google Cloud)
Experience and passion for data engineering in a big data environment using Cloud platforms such as GPC, GCC (i.e. AWS, Azure, Google Cloud)
Knowledge about system design, data structure and algorithms
Familiar with data modelling, data access, and data storage infrastructure like Data Mart, Data Lake, Data Virtualisation and Data Warehouse for efficient storage and retrieval
Familiar with rest api and web requests/protocols in general
Familiar with big data frameworks and tools (eg. Hadoop, Spark, Kafka,RabbitMQ)
Familiar with W3C Document Object Model and customized web scraping (e.g. BeautifulSoup, CasperJS, PhantomJS, Selenium, Nodejs, etc)
Familiar with data governance policies, access control and security best practices
Comfortable in at least one scripting language (eg. SQL,Python)
Comfortable in both windows and linux development environments

Benefits

Comp & perks

Empowering environment
Professional development opportunities