Senior Data Engineer at Smart Working | Remote Data Engineering Job

 

Smart Working is offering an opportunity for an experienced Senior Data Engineer to join a remote-first team and help build reliable, scalable data infrastructure for a growing global business.

The position is designed for an experienced data professional who can work across the complete data lifecycle, including data ingestion, transformation, modelling, cloud infrastructure, business intelligence, and analytics.

The successful candidate will work with technologies including Google BigQuery, Google Cloud Platform, Looker, LookML, SQL, ETL/ELT pipelines, Dataflow, Pub/Sub, Cloud Functions, and Cloud Composer.

This is a long-term position for someone who wants to take ownership of data architecture, establish engineering standards, improve data quality, and help business teams make better decisions using reliable data.

About Smart Working

Smart Working is a remote-first company focused on connecting skilled professionals with international companies and long-term career opportunities.

Rather than treating remote employment as simply working from home, Smart Working emphasizes community, professional development, employee well-being, mentorship, and long-term career growth.

The company aims to remove geographic barriers by connecting professionals with global teams and businesses that value their expertise.

Smart Working also promotes a culture centered around integrity, excellence, ambition, and belonging.

For professionals looking for a long-term remote career rather than short-term freelance projects, the company presents an opportunity to become part of a distributed team while working on meaningful business and technology projects.

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About the Senior Data Engineer Role

The Senior Data Engineer will be embedded within an engineering and analytics team and will contribute across the entire data lifecycle.

The role covers:

• Data ingestion
• Data transformation
• Data modelling
• Cloud infrastructure
• Business intelligence
• Data quality
• Data governance
• Analytics
• Architecture

The successful candidate will have significant ownership and will be expected to help shape data standards and architecture.

This makes the opportunity particularly suitable for senior professionals who enjoy solving complex data problems while also communicating with commercial, product, marketing, and other business teams.

Key Responsibilities

Build ETL and ELT Pipelines

One of the main responsibilities will be designing, developing, and maintaining reliable ETL/ELT pipelines.

These pipelines will move information from source systems into Google BigQuery, where it can be transformed and analyzed.

The successful candidate will need to ensure that pipelines are:

• Reliable
• Scalable
• Observable
• Maintainable
• Efficient

Monitoring and alerting will also be important to ensure that data problems are detected early.

Develop Data Models

The Senior Data Engineer will develop and enforce data modelling and schema standards.

This includes using best-practice SQL and dimensional modelling principles to create clear and reusable data structures.

Experience with star schemas and performance optimization is particularly important.

Well-designed data models will allow analysts and business users to access reliable information without repeatedly rebuilding the same transformations.

Manage Google BigQuery

The role includes ownership of the company's Google BigQuery environment.

Responsibilities will include optimizing queries, managing costs, enforcing data governance, and ensuring that the platform can scale as the business grows.

Candidates should therefore understand both the technical and financial considerations of running cloud-based data warehouses.

Develop Looker Dashboards

The Senior Data Engineer will work with Looker and LookML to turn complex datasets into useful business intelligence.

This includes building and maintaining:

• Looker Explores
• LookML models
• Business dashboards
• Data products
• Analytical reports

The objective is to make data understandable and actionable for non-technical stakeholders.

Work Across Google Cloud Platform

The position requires hands-on experience across the Google Cloud ecosystem.

The successful candidate will work with services including:

• Google Cloud Storage
• Dataflow
• Pub/Sub
• Cloud Functions
• Cloud Composer
• BigQuery

This provides an opportunity to design complete cloud-native data solutions rather than working with only a single component of the data stack.

Collaborate With Business Teams

Data engineering does not happen in isolation.

The Senior Data Engineer will work with analytics, engineering, commercial, product, and marketing teams to understand their data requirements.

The candidate will translate business problems into scalable technical solutions while clearly communicating technical limitations, timelines, and trade-offs.

Improve Data Quality

Reliable data is critical to business decision-making.

The role therefore includes implementing data-quality and testing frameworks, as well as monitoring and alerting systems.

The goal is to identify data problems quickly and ensure that stakeholders can trust the information being presented to them.

Documentation and Technical Standards

The successful candidate will contribute to documentation, coding standards, and architectural decision records.

This will help create consistency across the data team and make it easier for engineers and analysts to understand how the organization's data infrastructure works.

Mentor Junior Team Members

As a senior member of the team, the successful candidate will also mentor junior data professionals.

This involves sharing technical knowledge, reviewing approaches, and helping establish a high standard of engineering quality across the data function.

Requirements

Applicants should have substantial professional experience in data engineering and analytics.

The main requirements include:

• 5+ years of experience with SQL and data modelling
• Strong understanding of dimensional modelling
• Experience with star schemas
• Strong performance optimization skills
• 3+ years of production experience with Google BigQuery
• 3+ years of hands-on Google Cloud Platform experience
• 3+ years building ETL/ELT pipelines at scale
• At least 1 year of experience with Looker and LookML
• Experience delivering at least one data project from initial scope through completion
• Ability to communicate effectively with non-technical stakeholders
• Ability to make practical architecture decisions in a cloud-native environment

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Candidates should be comfortable taking ownership rather than waiting for detailed instructions.

Nice-to-Have Skills

Several additional skills can strengthen an application.

Experience with dbt (Data Build Tool) is advantageous, particularly for managing transformation layers and data testing.

Knowledge of Apache Airflow or Cloud Composer is also valuable for workflow orchestration.

Python experience can be useful for:

• Pipeline scripting
• Data validation
• Automation
• Data processing

Experience with retail, ecommerce, or fashion is another advantage because it provides an understanding of how data moves through commercial and digital channels.

Candidates with experience in real-time or streaming data using Pub/Sub or Dataflow may also be particularly competitive.

Additional desirable experience includes:

• Terraform
• Infrastructure as Code
• Data governance
• Data cataloguing
• Data lineage
• Modern data-stack technologies

Working Hours

The position operates on fixed shifts.

During summer, the working hours are:

12:00 PM – 9:30 PM IST

During winter, the working hours are:

1:00 PM – 10:30 PM IST

The company states that there is no weekend work, providing employees with a predictable Monday-to-Friday schedule and an emphasis on work-life balance.

Applicants should consider the working hours carefully based on their location and time zone before applying.

Benefits

Smart Working provides several benefits designed to support employees from the beginning of their employment.

Benefits include:

Laptop From Day One

Employees receive a laptop to support their remote work.

Medical Insurance

Full medical insurance is provided from the beginning of employment.

Mentorship

Employees have access to mentorship and opportunities to learn from experienced professionals.

Remote-First Community

Smart Working emphasizes community and connection despite operating remotely.

Employees can participate in forums where ideas, knowledge, and experiences are shared.

No Weekend Work

The company specifically highlights its commitment to work-life balance through a schedule that does not require weekend work.

Who Should Apply?

This position is particularly suitable for experienced professionals working as:

• Senior Data Engineer
• Data Engineer
• Analytics Engineer
• Cloud Data Engineer
• BigQuery Engineer
• Data Platform Engineer
• BI Engineer
• Data Warehouse Engineer
• Senior Analytics Engineer

Candidates with strong experience in BigQuery, GCP, SQL, ETL/ELT, Looker, and data modelling should consider applying.

How to Prepare Your Application

Before applying, tailor your CV specifically to the requirements of this position.

Make sure your technical skills are clearly visible.

Highlight experience with:

• SQL
• BigQuery
• Google Cloud Platform
• ETL/ELT
• Looker
• LookML
• Data modelling
• Dimensional modelling
• Data pipelines
• Data quality
• Cloud architecture
• Python
• dbt
• Airflow
• Data governance

Most importantly, demonstrate measurable results.

For example, mention how you reduced query costs, improved pipeline reliability, reduced data-processing time, automated manual processes, improved dashboard performance, or supported business growth through better data infrastructure.

Career Growth

The position can provide a strong foundation for professionals seeking advancement into senior technical and leadership positions.

Potential future career paths include:

• Lead Data Engineer
• Staff Data Engineer
• Data Engineering Manager
• Analytics Engineering Manager
• Data Architect
• Cloud Data Architect
• Head of Data Engineering
• Director of Data

Working across both engineering and business functions can also help professionals develop the communication and leadership skills required for senior data roles.

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Master in-demand skills with expert-led courses on Programming, AI, Data Science, Business, Finance, Marketing, Design and thousands more.

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How to Apply

Professionals interested in this opportunity should review the latest application instructions and submit their CV through the relevant Smart Working recruitment channel.

Application Link:

Applicants should verify the current status of the vacancy before applying, as remote job listings can close or change their requirements.

Final Thoughts

The Senior Data Engineer opportunity at Smart Working is an attractive option for experienced data professionals who want to work remotely while taking ownership of modern cloud data infrastructure.

The role combines data engineering, cloud computing, business intelligence, data modelling, and architecture, making it broader than a traditional data pipeline position.

With technologies such as Google BigQuery, GCP, Looker, Dataflow, Pub/Sub, Cloud Functions, and Cloud Composer, the successful candidate will work with a modern data stack while collaborating directly with business stakeholders.

For professionals with several years of experience in SQL, BigQuery, GCP, ETL/ELT, and Looker who are looking for a long-term remote career, this opportunity could be a strong next step.

Smart Working's emphasis on mentorship, medical insurance, equipment, predictable working hours, and no weekend work also makes the position worth considering for experienced data professionals seeking both career growth and work-life balance.