OneMagnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter customer experiences and delivering highly integrated solutions across digital, media, and technology. By combining deep industry expertise with advanced analytics and artificial intelligence, we enable our clients to make better decisions, move faster, and compete more effectively in dynamic markets.
We are seeking an experienced and highly skilled Senior Data Engineer to lead the design, development, and implementation of enterprise-scale cloud data solutions. This role is responsible for architecting modern data platforms, building scalable ETL/ELT frameworks, and delivering high-performance analytics solutions on Google Cloud Platform (GCP).
The Senior Data Engineer is a technical leader and strategic contributor responsible for designing and governing modern data solutions across the organization. You will collaborate closely with Product Managers, Product Owners, Software Engineers, Data Architects, Analytics Teams, and Business Stakeholders to transform complex business requirements into scalable, secure, and performant data platforms.
You have extensive experience architecting and operationalizing large-scale data ecosystems, including Data Lakes, Data Warehouses, Data Marts, and Analytics Platforms within GCP. You possess strong leadership capabilities, excellent stakeholder management skills, and a passion for mentoring engineering teams while driving technical excellence.
The Impact You’ll have:
As a Senior Data Engineer, you will provide technical leadership across the data ecosystem, drive engineering best practices, mentor team members, and collaborate with cross-functional stakeholders to transform business requirements into scalable, secure, and reliable data products. You will play a critical role in shaping the organization's data strategy and enabling data-driven decision-making through modern cloud technologies and innovative engineering practices.
The ideal candidate possesses deep expertise across modern data engineering technologies, strong architectural skills, and proven experience leading teams in designing and delivering large-scale cloud data platforms.
What You’ll Do:
Data Platform Architecture & Engineering- Design, develop, and maintain scalable cloud-native data platforms on Google Cloud Platform (GCP).
- Architect enterprise Data Lakes, Data Warehouses, Data Marts, and Analytics Platforms.
- Build robust, reusable, and metadata-driven ETL/ELT frameworks.
- Develop high-volume data pipelines capable of supporting large-scale analytics and reporting workloads.
- Implement event-driven and batch-processing architectures using modern cloud services.
- Collaborate with Data Architects to define enterprise data models, integration patterns, and platform strategies.
- Provide technical leadership, mentorship, and coaching to Data Engineers and ETL developers.
- Establish data engineering best practices, coding standards, CI/CD frameworks, and governance processes.
- Ensure data quality, observability, monitoring, lineage, governance, and security across all data products.
- Drive performance optimization initiatives for BigQuery workloads and cloud infrastructure costs.
- Evaluate emerging technologies, including AI/ML and Generative AI solutions, and recommend adoption strategies.
- Partner with business stakeholders to translate requirements into scalable technical solutions.
- Lead code reviews, architecture reviews, and technical design sessions.
- Identify and mitigate delivery risks while ensuring successful project execution.
- Support production environments through proactive monitoring, troubleshooting, and root-cause analysis.
Technical Leadership
- Provide technical leadership and architectural guidance to Data Engineers and ETL developers.Establish engineering standards, coding best practices, design patterns, and governance frameworks
- Conduct architecture reviews, code reviews, and technical design sessions.
- Mentor team members and support skill development across the engineering organization.
What You'll Need:
- Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field.
- 8+ years of overall experience in Data Engineering, ETL/ELT development, and data platform delivery.
- 5+ years of hands-on experience in Google Cloud Platform (GCP).
- Extensive experience designing and building enterprise-scale Data Warehouses, Data Lakes, and Analytics Platforms.
- Expert-level SQL skills with experience in performance tuning and optimization.
- Strong expertise in Python and modern data engineering frameworks.
- Hands-on experience with: BigQuery Google Cloud Storage (GCS) Dataflow Dataproc Cloud Run Pub/Sub Cloud Composer / Apache Airflow Cloud Functions Experience building CI/CD pipelines using GitHub, Terraform, Tekton, and Infrastructure-as-Code practices.
- Strong understanding of distributed data processing and cloud-native architectures.
- Experience implementing data quality, testing, observability, and monitoring frameworks.
- Knowledge of data governance, security, privacy, and compliance best practices.
- Experience working within Agile, Scrum, and Lean methodologies.
- Proven ability to manage multiple stakeholders and drive technical discussions.
Future-Ready Skills (Nice to Have):
- Google Cloud Professional Data Engineer Certification.
- Google Cloud Associate Cloud Engineer Certification.
- Experience with Qlik Sense, Looker, Power BI, or other BI and Analytics tools.
- Experience with Snowflake, Databricks, or other modern data platforms.
- Exposure to AI, Machine Learning, Generative AI, and Large Language Models (LLMs).
- Experience leading onshore and offshore engineering teams.
Benefits
We offer a comprehensive benefits package including Medical Insurance, PF, Gratuity, paid holidays, and more.
We are an equal opportunity employer
We believe that Innovative ideas and solutions start with unique perspectives. That’s why we’re committed to providing every employee a workplace that’s free of discrimination and intolerance. We’re proud to be an equal opportunity employer and actively search for like-minded people to join our team.
Skills Required
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field
- 8+ years of experience in data engineering, ETL/ELT development, and data platform delivery
- 5+ years of hands-on experience with Google Cloud Platform
- Experience designing and building enterprise-scale data warehouses, data lakes, and analytics platforms
- Expert-level SQL skills, including performance tuning and optimization
- Strong Python expertise and experience with modern data engineering frameworks
- Hands-on experience with BigQuery, Google Cloud Storage, Dataflow, Dataproc, Cloud Run, Pub/Sub, Cloud Composer or Apache Airflow, and Cloud Functions
- Experience building CI/CD pipelines with GitHub, Terraform, Tekton, and infrastructure-as-code practices
- Strong understanding of distributed data processing and cloud-native architectures
- Experience implementing data quality, testing, observability, and monitoring frameworks
- Knowledge of data governance, security, privacy, and compliance best practices
- Experience with Agile, Scrum, and Lean methodologies
- Ability to manage multiple stakeholders and lead technical discussions
- Google Cloud Professional Data Engineer Certification
- Google Cloud Associate Cloud Engineer Certification
- Experience with Qlik Sense, Looker, Power BI, or other BI and analytics tools
- Experience with Snowflake, Databricks, or other modern data platforms
- Exposure to artificial intelligence, machine learning, generative AI, and large language models
- Experience leading onshore and offshore engineering teams
OneMagnify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about OneMagnify and has not been reviewed or approved by OneMagnify.
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Parental & Family Support — Parental support is positioned as a defined benefit with six weeks of 100% paid parental leave plus employer-paid short-term disability. Parental leave sentiment is characterized as middling, but the policy itself is clearly specified as part of the package.
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Wellbeing & Lifestyle Benefits — Work flexibility is framed as a meaningful part of the total rewards experience through hybrid/remote options and flexible time off with paid sick leave. Added lifestyle-oriented perks such as volunteer PTO, pet insurance, legal assistance, ERGs, recognition programs, and partner discounts broaden the offering beyond core insurance.
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Flexible Benefits — A broad slate of optional add-ons and programs is described, including tuition reimbursement up to $5,250/year and other elective-style perks. This variety can help different employee needs be met even when base pay competitiveness is seen as only average.
OneMagnify Insights
What We Do
We are technologists, strategists, and creative minds dedicated to moving brands forward with work that delivers results. Our messaging, communications and design are driven by human insights and fresh ideas because starting a conversation is one thing, but building a lasting relationship is another.
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