We are looking for a hands-on, data-obsessed leader to build and own Opptras external data intelligence layer the crawling, collection, structuring, and delivery of market, competitor, and category data that powers critical business decisions across the company. This data, combined with Opptras internal operational data, will feed into analytics and decision systems used by multiple teams across platforms and geographies.

This is not a reporting role. You will architect and build the data pipelines, crawlers, and real-time feeds that become a core competitive advantage for Opptra enabling everything from what to buy and how to price it, to which brands to onboard in which country.

What Youll Own :

1. External Data Collection & Crawling Infrastructure :

- Design, build, and maintain scalable crawling systems to collect structured data from marketplaces (Amazon, Flipkart, Shopee, Lazada, Noon, etc.), competitor sites, and public data sources across India, SEA, and GCC.

- Data to be collected includes (but is not limited to) :

- Product listings, pricing, promotions, and discounts across platforms

- Category rankings, bestseller lists, search result positions

- Competitor assortment, new launches, and catalogue changes

- Customer ratings, reviews, and sentiment signals

- Ad placement data, sponsored product visibility, and share-of-voice metrics

- Brand presence and market penetration signals by country

- Handle anti-scraping mechanisms, rate-limiting, geo-restrictions, and platform-specific nuances across 15+ marketplace environments.

- Build real-time and near-real-time data feeds where speed of insight matters (e.g.,competitor price changes, flash sale monitoring, ad bid landscapes).

2. Data Structuring, Quality & Enrichment :

- Normalize and structure heterogeneous data from diverse platforms into a unified, queryable data layer that different teams can consume reliably.

- Build entity resolution and matching systems to map products, brands, and categories consistently across marketplaces and regions.

- Implement data quality monitoring, anomaly detection, and freshness tracking to ensure data reliability for downstream decision-making.

- Enrich external data with taxonomy, categorization, and metadata tagging relevant to Opptras category focus (consumer electronics, home & kitchen, babycare, FMCG, etc.).

3. Decision Support Across Business Functions :

The data you collect and organize will directly power decisions across :

- Performance Marketing Competitor ad spend signals, keyword opportunity mapping, category share-of-voice, price position relative to competition feeding real-time bidding and budget allocation decisions.

- Pricing & Promotions : Competitive price monitoring, discount depth analysis, marketplace fee structures, and margin-optimal price recommendations across platforms and regions.

- Buying & Inventory : Demand signals from search trends, bestseller velocity, seasonal patterns, and category growth indicators to inform what to buy, how much, and when.

- Brand Onboarding : Market attractiveness scoring by country and category, whitespace identification, competitive landscape assessment, and brand-market fit analysis to guide which brands to pursue and where.

- Category Intelligence : Category size estimation, growth trajectories, consumer preference shifts, and regulatory landscape changes across target markets.

4. Integration with Internal Data & Analytics :

- Work closely with internal data engineering and analytics teams to combine external intelligence with Opptras operational data (sales, inventory, logistics, marketing performance).

- Build unified data products and dashboards that give platform teams, country heads, and category managers a single view combining market context with internal performance.

- Ensure data pipelines are production-grade, well-documented, and serve both batch analytics and real-time operational needs.

5. Scale & Innovation :

- Continuously expand coverage to new platforms, data sources, and geographies as

Opptra scales.

- Explore and integrate alternative data sources (social listening, creator/influencer performance data, regulatory databases, trade data).

- Leverage AI/ML to automate data extraction from unstructured sources, improve entity matching, and generate predictive signals from collected data.

What Were Looking For :

- 5 to 10 years of experience in data engineering, web scraping/crawling at scale, or market data infrastructure roles.

- Deep hands-on expertise with large-scale crawling frameworks (Scrapy, Playwright, Puppeteer, or custom solutions) and techniques to handle dynamic pages, CAPTCHAs, and anti-bot measures.

- Strong proficiency in Python and SQL; experience with data pipeline orchestration tools (Airflow, Dagster, or similar).

- Experience building and operating real-time or near-real-time data pipelines (Kafka,Flink, or equivalent).

- Proven track record of collecting, structuring, and delivering e-commerce or marketplace data at scale.

- Experience with cloud infrastructure (AWS preferred) for deploying and scaling crawling workloads.

- Strong understanding of data quality, monitoring, and observability practices.

Strong Plus :

- Experience working with Asian marketplace platforms (Amazon India, Flipkart, Shopee, Lazada, Noon) and understanding their data structures.

- Background in e-commerce, retail analytics, or competitive intelligence.

- Experience applying ML/NLP for entity matching, product categorization, or sentiment analysis on marketplace data.

- Familiarity with pricing optimization, assortment planning, or demand forecasting use cases.

- Exposure to multiple Asian markets and understanding of regional platform variations.

The Mindset We Value :

- You want to create systems from scratch, not just maintain them. Builder mentality

- You understand that stale data is worse than no data.Obsession with data freshness and accuracy

- You can translate a pricing teams question into a data pipeline spec.Cross-functional fluency- marketplace ecosystems change constantly; you adapt fast.

- Comfort with ambiguityyou think about data as a product, not just a feed.Ownership orientation

Why Opptra :

- Build the data backbone of Asias most ambitious brand distribution platform, operating across three of the worlds fastest-growing consumer regions.

- Work alongside a leadership team from Flipkart, Amazon, Apple, Swiggy, and Reliance who understand the power of data-driven operations at scale.

- Your work will directly influence millions of dollars in buying, pricing, and marketing decisions across 28+ global brands.

- Early-stage impact with real infrastructure Opptra has the operational scale (18 warehouses, 15+ platforms) but the data intelligence layer is being built ground-up.