Senior Architect

Tredence Inc.; Bengaluru; On-site; INR 6,000,000 - 9,000,000; Full time

Job summary

Tredence Inc. is seeking a Senior Data Engineering Architect to spearhead the design and execution of our enterprise data platform for retail analytics. You will architect scalable batch and streaming pipelines on GCP, code in Scala with Spark, and shape semantic models for Looker and Power BI.

You will mentor engineers and drive governance and testing practices across analytics delivery. Ideal candidates bring hands-on experience with large datasets, low-latency reporting, and strong

Qualifications

• Extensive experience designing large-scale data pipelines for retail domains.
• Proficient in Spark-based processing using Scala.
• Strong knowledge of data modeling and BI semantic layers.
• Experience with CI/CD for data pipelines and quality testing.

Responsibilities

• System Design: Architect, scale, and maintain robust batch and streaming pipelines on GCP (Dataproc, GCS, BigQuery).
• Code Execution & Development: core pipeline development using Scala and Apache Spark with automated tests.
• Pipeline Optimization: performance tuning, memory management, and efficient cloud resource usage.
• Semantic Modeling & BI Layer Architecture: design Looker LookML and Power BI models for enterprise analytics; optimize dashboards.
• Retail Analytics & Business Enablement: align data models with retail domain needs and enable actionable insights for stakeholders.
• Technical Leadership & Governance: establish standards for data modeling, ETL/ELT, CI/CD, monitoring, data quality, and mentorship.

Skills

Scala

Apache Spark

Data modeling

CI/CD

Tools

GCP Dataproc

GCS

BigQuery

Looker LookML

Power BI

DAX

Job description

Location – Bangalore, Chennai, Pune, Kolkata and Gurugram

We are seeking a Senior Data Engineering Architect with extensive expertise in large-scale data processing, enterprise pipeline design, and business intelligence architecture within the retail domain.

In this role, you will lead the end-to-end design and execution of our enterprise data platform, processing high-volume retail transactions, customer interactions, and inventory feeds. You will bridge the gap between heavy-duty Data Engineering (using Scala, Apache Spark, and GCP Dataproc) and Business Intelligence delivery (via Power BI, Looker semantic models, and executive dashboards). The ideal candidate brings a proven track record of architecting performant pipelines for massive datasets while ensuring seamless, high-speed reporting for analytical end-users.

Key Responsibilities

• System Design: Architect, scale, and maintain robust, fault-tolerant batch and streaming data pipelines on Google Cloud Platform (GCP) using GCP Dataproc, GCS, and BigQuery.
• Code Execution & Development: Core pipeline development using Scala and Apache Spark, enforcing high coding standards, modular design patterns, and automated testing strategies.
• Pipeline Optimization: Conduct deep performance tuning on Spark jobs, memory management, shuffle partitioning, and execution plans to ensure ultra-low execution latency and cost-effective cloud resource usage.

2. Semantic Modeling & BI Layer Architecture

• Semantic Layer Design: Build, standardize, and govern unified semantic models in Looker (LookML) and Power BI (Tabular Models / DAX) for enterprise-wide analytics.
• Dashboard & Report Engineering: Partner with analytical teams to translate retail business requirements into performant, intuitive reporting interfaces and dashboards.
• Query Performance Tuning: Optimize BI connection modes (DirectQuery, Import, Dual Mode, Aggregation Tables) and underlying data store schemas to support sub-second dashboard load times across massive datasets.

3. Retail Analytics & Business Enablement

• Domain Alignment: Leverage deep retail domain expertise (e.g., POS data, inventory management, customer 360, supply chain, store operations, and promotional effectiveness) to design logical data models that reflect business realities.
• Insight Delivery: Collaborate with business analysts and decision-makers to transform complex datasets into actionable operational and executive insights.

4. Technical Leadership & Governance

• Standards & Best Practices: Establish technical standards for data modeling, ETL/ELT development, code reviews, CI/CD deployment, and monitoring.
• Data Quality & Governance: Implement data lineage, metadata management, and automated data validation rules to guarantee data integrity across downstream reports.
• Mentorship: Provide architectural guidance and technical mentorship to senior and staff data engineers.

There is a reason we are one of the fastest growingprivate companies in the country!You will have theopportunity to work with some of the smartest, friendliest, hardest working peoplein the data analytics space. You will work with the latest technologies and interface directly with the key decision stakeholders at our clients,some of the largest and most innovative businesses in the world. We offer a 401k match; full medical, dental and vision benefits, a fun team atmosphere and a work life balance. Our people are our greatest asset and we value every one of them. Come see why we’re so successful in one of the most competitive and fastest growing industries in the world.

Tredence 5 core values

• Think Impact
• Constantly curious
• Do the right thing

Tredence is an equal opportunity employer. We celebrate and support diversity and are committed to creating an inclusive environment for all employees.