Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their team's hybrid work schedule requirements.

About the Role : As a Senior Data Engineer, you will be part of the Data Engineering team with this role being inherently multi-functional, and the ideal candidate will work with Client Experience, Data Scientist, Analysts, Application teams across the company, as well as all other Data Engineering squads at Wayfair. We are looking for someone with a love for data, handling ambiguous requirements and the ability to iterate quickly. Successful candidates will have strong engineering skills and communication and a belief that data-driven processes lead to phenomenal products.

What you'll do: Drive the

end-to-end design and evolution

of data models, pipelines, and data products for Search, Recommendations, and Marketing—operating at scale and influencing multiple domains. Own the development of

scalable, batch-first data systems

that ingest and transform structured, semi-structured, and unstructured data into

high-quality, AI-consumable representations

(e.g., curated datasets, embeddings-ready data, feature layers, and semantic abstractions). Design and build

high-fidelity data pipelines

optimized for reliability, cost, and performance, with a focus on

efficient retrieval, data freshness, and contextual usability

for downstream systems. Build and maintain

robust data models

including fact/dimension models, SCDs, CDC pipelines, and

data versioning strategies

to ensure consistency and reproducibility. Contribute to the development of a

unified semantic layer

that bridges raw data and AI/ML systems,



enabling standardized metrics, reusable data definitions, and improved data access patterns. Work with

metadata, lineage, and data discovery frameworks

to improve transparency, governance, and usability of data across the organization. Partner cross-functionally with Product, Analytics, and Data Science to

translate ambiguous business problems into well-defined data solutions and reusable data assets . Define and enforce

data modeling standards, data contracts, and quality frameworks

across teams. Drive improvements in

data observability, SLA/SLO adherence, and pipeline reliability

across the ecosystem. Make architectural decisions and trade-offs across

storage, compute, and orchestration layers

within a GCP-native stack.

What You'll Need: Bachelor’s/Master’s degree in Computer Science or related field, or equivalent experience. ~11 years of experience

in Data Engineering, building and owning large-scale data platforms and datasets at scale. Deep expertise in

data modeling

(dimensional models, SCDs, wide tables), along with strong understanding of

CDC, data versioning, and incremental processing strategies . Strong experience designing and building

data pipelines

on Google Cloud Platform using Google BigQuery and Google Cloud Storage. Advanced proficiency in





SQL and Python , with a robust focus on

query optimization, cost efficiency, and large-scale data processing . Solid understanding of

data lakehouse principles , storage formats (e.g., Parquet), partitioning, clustering, and performance tuning. Experience building

reliable, production-grade data systems , including ingestion, transformation, serving layers, and strong

data quality and observability practices (SLAs/SLOs) . Experience with event-driven and streaming architectures

(e.g., Pub/Sub, Kafka), with the ability to apply them pragmatically alongside where needed. Experience enabling AI/ML use cases from a data perspective , including preparing high-quality datasets for model consumption, supporting feature engineering workflows, and building

semantic or context-rich data layers

that improve downstream usability. Familiarity with concepts such as

metadata management, data lineage, and data discovery , and their role in improving trust and usability of data platforms. Proven ability to

translate ambiguous business requirements into scalable data models and systems , especially in domains like search, recommendations, or marketing analytics. Demonstrated ownership of

large problem spaces end-to-end , with the ability to influence architecture, drive standards, and align multiple teams. Experience providing

technical leadership and mentorship , setting best practices, and raising the bar for engineering quality. Strong communication skills with the ability to

articulate technical decisions, trade-offs, and system designs

to diverse stakeholders.

📌 Senior Data Engineer (Mumbai)
🏢 Wayfair
📍 Mumbai