Senior Data Engineer

Overview

Synoptek
We are seeking a highly skilled Senior Analyst, BI & Data Insights to join our growing team. In this critical role, you will play a key role in building and maintaining a best-in-class data platform that drives innovation and growth for our transportation and logistics business. You will leverage your expertise in end-to-end Azure data engineering, Snowflake, and a variety of data engineering tools to design, develop, and implement scalable data pipelines for ingesting, transforming, and loading (ETL/ELT) large datasets.

You will partner closely with stakeholders across the organization to understand their needs and translate them into clear and concise data visualizations through Data engineering solution.
 
Role Overview:
The ideal candidate will have 6 to 8 years of hands-on experience designing, building, and maintaining scalable data pipelines and cloud-based data platforms, with a solid understanding of Medallion Architecture (Bronze, Silver, Gold) for organizing and delivering reliable, governed data across the organization. You will collaborate closely with business stakeholders to ensure the reliable delivery of high-quality data across the organization.
 
Beyond individual contribution, this role carries meaningful technical leadership responsibilities like mentoring junior and mid-level data engineers, establishing platform standards, driving architectural decisions, and delivering high-quality, business-critical data assets. It also offers an exciting opportunity to work with modern data technologies including Snowflake, Databricks, and real-time streaming architecture.

Responsibilities

Key Responsibilities:
Own the end-to-end design and evolution of the Medallion Architecture - defining ingestion patterns for Bronze, transformation and data quality standards for Silver, and data product delivery conventions for Gold, ensuring consistency across all platforms and teams
Design, develop, and maintain scalable, high-performance data pipelines following Medallion Architecture and ETL/ELT workflows for batch and real-time data ingestion
Develop and optimize Snowflake schemas, views, and data models aligned with the Medallion pattern to support analytical workloads and self-service reporting
Build and optimize data models, tables, and views within Snowflake aligned with the Medallion pattern to support analytical and operational use cases
Lead the design and implementation of real-time streaming data solutions to enable low-latency data availability across the organization
Develop and manage Databricks workflows, notebooks, and Delta Lake pipelines for large-scale data processing
Establish and maintain data governance practices across all Medallion tiers — including Unity Catalog policies, Snowflake RBAC, and data lineage tracking
Mentor and technically guide junior and mid-level data engineers through code reviews, design reviews, pairing sessions, and documentation
Collaborate with business stakeholders to understand requirements and deliver reliable, well-documented data products
Apply CI/CD best practices and manage code through Git version control.
Monitor, troubleshoot, and optimize data pipeline performance, and ensuring data quality
Collaborate with business stakeholders to understand requirements and deliver reliable, well-documented data products
Willingness to participate in developing the AI agents
 

Qualifications

 
Experience:
6 to 8 years of professional experience in data engineering or a related field
Proven track record working with cloud-native data platforms (Snowflake, Databricks, or equivalent)
Deep, production-proven expertise in designing and operating Medallion Architecture (Bronze/Silver/Gold) at scale using Databricks Delta Lake and/or Snowflake multi-layer schemas
Extensive experience with Snowflake — advanced data modelling, performance optimisation, dynamic data masking, and row-level security
Strong expertise in Databricks — cluster management, Delta Live Tables, and Unity Catalog
Experience with real-time and streaming data architectures in production environments
Knowledge of data orchestration tools such as Azure Data Factory
Hands-on experience designing and building ETL/ELT pipelines for large-scale data environments
Familiarity with data warehousing concepts, dimensional modeling, and data lake architecture
Experience working in Agile/Scrum development environments
Exposure to CI/CD pipelines and DevOps practices for data workflows
Proficiency in PySpark and/or Python for data transformation and pipeline development
Strong SQL skills including query optimization, window functions, and complex joins
Experience with cloud platforms such as Azure, AWS, or GCP
Skills/Attributes
Synoptek core DNA behaviors:Clarity: Possesses excellent communication skills, makes a concentrated effort to speak the customer’s language. Ability to field questions with concise, well-constructed responses
OwnIT: Shows integrity, innovation, and accountability in completing daily assignments
Results: Solutions focused and driven to resolve conflict quickly and precisely. Proactively looks for opportunities to contribute to the company’s business goals
Growth: Willing to learn and ask questions.

Constantly looking for new ways to improve yourself. Ability to adapt and grow in a fast-paced environment
Team: Embraces both customers and colleagues as team members. Ability to be flexible, respectful, engaged and collaborative

Working Conditions
We live by the motto ‘work hard, play hard’ and strive to support our employees in both their professional and personal goals. We believe that by hiring the right people, leading process improvement, and leveraging technology, we achieve superior results. Work is performed primarily in an office or remote environment.

May be subject to time constraints and tight deadlines. May require occasional travel.
 
EEO Statement
We are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, veteran status, sexual orientation, gender identity, marital status, pregnancy, genetic information, or any other characteristic protected by law and will not be discriminated against on the basis of disability.

It is our intention that all qualified applicants are given equal opportunity and that employment decisions be based on job-related factors.