Data Engineer
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Posted on:
Yesterday
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1 Vacancy
Job Summary
About WebEngage:
WebEngage is an enterprise-grade customer engagement and retention platform that helps global brands across industries such as e-commerce fintech travel edtech gaming media and consumer apps. and turn data into measurable revenue impact. Trusted by 800 brands globally we have strong presence in India UAE KSA SEA Europe and beyond. WebEngage powers intelligent real-time engagement across the entire customer lifecycle.
- We are built for scale.
- We are built for complexity.
- We are built for outcomes.
At our core WebEngage is a full-stack retention operating system that combines:
- A powerful Customer Data Platform (CDP)
- Real-time behavioral segmentation and intelligence
- Omnichannel journey orchestration
- AI-driven personalization and recommendations
- Deep analytics experimentation and revenue attribution
- WebEngage BLACK: our AI-native layer that brings Agentic capabilities to engagement.
About The Role:
WebEngages Data Engineering team is the backbone of our analytics personalisation and machine-learning capabilities. As a Data Engineer you will own the end-to-end lifecycle of data from ingesting raw event streams and third-party feeds to building well-modelled highly reliable datasets that power dashboards predictive models and customer journey orchestration. This is a high-impact hands-on role where you will work at the intersection of product analytics and backend engineering. You will be expected to think beyond just moving data designing for data quality pipeline observability cost efficiency and long-term maintainability from day one.
Responsibilities:
Pipeline Development & Reliability
- Design build and maintain production-grade ETL/ELT pipelines that ingest data from APIs databases event streams (Kafka/Pub-Sub) and flat files into the central data warehouse.
- Implement idempotent incremental load patterns with built-in retry logic dead-letter queues and SLA-based alerting to ensure zero-data-loss pipelines.
- Own pipeline observability set up data freshness checks row-count validations schema drift detection and anomaly alerts using tools like Great Expectations or dbt tests.
Data Modelling & Warehouse Design
- Translate business requirements into clean dimensional models (star/snowflake schemas) and maintain a well-documented data catalogue.
- Design slowly changing dimensions (SCD Type 1/2) bridge tables and fact tables optimised for analytical query patterns.
- Enforce partitioning clustering and materialised view strategies to keep warehouse costs under control while maintaining sub-second query performance.
Code Quality & Engineering Best Practices
- Write clean modular well-tested Python and SQL code. Follow DRY principles use version control (Git) and participate in peer code reviews.
- Build reusable transformation frameworks using dbt or equivalent tooling with proper documentation and testing at every layer (staging intermediate mart).
- Containerise data services with Docker and automate deployments via CI/CD pipelines (GitHub
Actions / GitLab CI).
BI Visualization & Analytics
- Build interactive dashboards and analytical tools using Streamlit enabling stakeholders to explore metrics run ad-hoc analyses and make data-driven decisions without engineering dependency.
- Design and maintain BI layers semantic models KPI definitions and pre-aggregated mart tables that serve as the single source of truth for reporting across teams.
- Translate raw data into compelling visual narratives using libraries like Plotly Matplotlib or Altair; present findings to both technical and non-technical audiences.
Collaboration & Communication
- Partner with product managers analysts and data scientists to understand data needs and proactively identify gaps in current data coverage.
- Document data lineage transformation logic SLAs and known limitations in a shared knowledge base to enable self-service analytics.
- Contribute to internal engineering guilds knowledge-sharing sessions and post-incident reviews for pipeline failures.
Requirements:
- Strong SQL skills with expertise in complex queries performance optimization and cost-efficient design on cloud data warehouses (BigQuery Redshift).
- Strong Python scripting for data ingestion transformation and validation with hands-on experience in Pandas SQLAlchemy APIs and automation.
- ETL/ELT- End-to-end ownership of data pipelines including ingestion transformation and loading with understanding of incremental loads and backfills.
- Data Modelling- Ability to design dimensional and transactional data models (star/snowflake SCDs) and translate business needs into optimized table structures.
Good to Have:
- Airflow dbt Docker CI/CD
- GCP/AWS data warehousing concepts
- BI tools / Streamlit / visualization
Qualifications:
- Bachelors degree in Computer Science Engineering Mathematics Statistics or a related quantitative field (or equivalent practical experience).
- 13 years of professional experience in data engineering analytics engineering or a backend role with significant data pipeline work.
- Strong understanding of data warehouse architecture know when to use wide denormalised tables vs. normalised models and the trade-offs of each.
- Familiarity with version control workflows (Git branching strategies pull requests code reviews) and agile development practices.
- A data quality mindset you instinctively validate assumptions add assertions to pipelines and treat silent data failures as critical incidents.
Life at WebEngage:
- We take transparency very seriously. Along with a full view of team goals get a top-level view across the board with our monthly & quarterly town hall meetings.
- A highly inclusive work culture that promotes a relaxed creative and productive environment.
- Practice autonomy open communication growth opportunitieswhile maintaining a perfect work-life balance
Perks & Benefits:
- Learning is a way of life. Unlock your full potential backed with cutting-edge tools and mentorship (Macbook for Engagers!)
- Get the best in class medical insurance (with Covid Care facilities) programs for taking care of your mental health and a Contemporary Leave Policy (beyond sick leaves)
Explore more here:
WebEngage aims to be an equal opportunity employer. We strongly believe that when people feel respected and included they can be more creative innovative and successful. We believe that change is the only constant and are in the process and will continue to be in process with changing times to adapt and advance diversity and inclusion. We take affirmative action to ensure equal opportunity and complete non-disclosure of all applicants without any regard to race color religion sex sexual orientation gender identity national origin disability Veteran status or any other characteristics not mentioned hereinabove which are protected under the law of the soil.
Required Experience:
IC
Key Skills
About Company
WebEngage offers CDP, Omnichannel Campaign Manager and Web & App Personalization Engine - to help brands boost their revenue from existing customers.
