Senior Data Engineer: Build Scalable Pipelines & ML Interfaces

Convo

Islamabad

Sur place

PKR 3 000 000 - 4 000 000

Plein temps

14 jours+

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Résumé du poste

CONVO is seeking a Senior Data Engineer to build reliable data pipelines and connectors powering its CPG-focused agentic platform. You’ll develop scalable batch and streaming pipelines using Python, Spark, Databricks, Kafka, dbt, and Delta Lake, transforming source data into governed RAW and CUBE layers while ensuring data quality, performance, observability, and reliability.

You’ll also build data-product interfaces that enable ML models, agents, and downstream applications to consume trusted

Qualifications

  • 5+ years in data engineering, with 3+ years delivering production Spark or Python pipelines.
  • Strong Python and production Spark/Databricks development.
  • Experience with Kafka or comparable event streaming technology.
  • Strong SQL performance tuning and dimensional/data-product implementation.
  • Familiarity with dbt and Delta Lake, including incremental patterns.

Responsabilités

  • Develop Python/Spark ingestion and transformation pipelines from source systems into RAW and Enriched CUBE layers.
  • Implement streaming paths alongside scheduled workloads.
  • Create dbt/SQL transformations, data-quality controls and contract-validation checks.
  • Optimize Delta Lake layout, SQL performance, partitioning and incremental processing.
  • Build feature-serving and data-product interfaces for models, agents and applications.
  • Instrument pipelines for lineage, freshness, throughput, failure recovery and cost.

Connaissances

Python
Spark
SQL
Data quality
Observability
Batch processing
Streaming

Outils

Databricks
Kafka
dbt
Delta Lake

Description du poste

CONVO is seeking a Senior Data Engineer to build reliable data pipelines and connectors powering its CPG-focused agentic platform. You’ll develop scalable batch and streaming pipelines using Python, Spark, Databricks, Kafka, dbt, and Delta Lake, transforming source data into governed RAW and CUBE layers while ensuring data quality, performance, observability, and reliability.

You’ll also build data-product interfaces that enable ML models, agents, and downstream applications to consume trusted

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