About the job
Must-Have Skills
- 5+ years in data architecture / data engineering, with at least 2+ years in an architect or lead capacity
- Strong SQL — advanced query optimization, indexing, partitioning strategies
- Data modeling — dimensional modeling (star/snowflake schema), normalization/denormalization tradeoffs, entity relationship design
- Cloud data platforms — hands-on with AWS (Redshift, S3, Glue), Azure (Synapse, Data Factory), or GCP (BigQuery, Dataflow)
- Big data ecosystems — Spark, Hadoop, or Kafka for large-scale/streaming data
- Data warehousing — Snowflake, Redshift, BigQuery, or Databricks
- ETL/ELT pipeline design — Airflow, dbt, Fivetran, or similar orchestration tools
- Data governance & security — data lineage, access control, compliance (GDPR/SOC2), master data management
Strongly Preferred
- Experience architecting systems supporting ML/AI pipelines (feature stores, vector DBs, real-time inference data flows)
- Programming — Python or Scala for pipeline development
- API/microservices architecture exposure — understanding how data systems integrate with application layers
- Experience with data mesh / data lake house architectures
- Prior experience presenting architecture decisions to leadership/stakeholders

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Company Brand Name: BikeFixup
Location: Faridabad
Work Mode: Work from Office
Working Days: 6 Days a Week (Rotational Off)*
Key Responsibilities:
Sales Responsibilities:
Achieve monthly sales targets for memberships.
Conduct outbound and inbound calls to pitch plans and convert inquiries into sales.
Provide detailed product knowledge and promote BikeFixup’s services effectively.
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Handle customer inquiries and resolve issues promptly with a professional attitude.
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Address complaints or concerns and escalate unresolved issues to the appropriate team.
Follow up with customers post-service to ensure a high level of satisfaction and identify areas for improvement.
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Strong communication skills in Hindi & English.
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Basic computer knowledge for lead tracking and reporting.
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Fixed salary + performance-based incentives.
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