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6-8 Years
Not Disclosed
Early Applicant
  • Posted 6 days ago
  • Be among the first 10 applicants

Job Description

Job Description:

  • 6+ years of experience in Data Engineering.
  • Strong data architecture and system design skills with the ability to make sound trade-offs around data modeling, partitioning, and scalability.
  • Demonstrated end-to-end ownership of production data pipelines, including design, deployment, monitoring, and operational support.
  • Expertise in Python and SQL as primary tools; experience with Hive/Hadoop is a plus.
  • Strong focus on data quality, validation, reconciliation, anomaly detection, and audit ability.
  • Experience working with finance, risk, compliance, or other highly regulated data domains requiring strong data lineage and governance.
  • Proven experience designing and building transaction and fact tables.
  • Advanced SQL skills, including window functions, CTEs, CASE statements, and working across MySQL/PostgreSQL environments.
  • Strong Python expertise, including pandas, SQLAlchemy, type hints, data classes, and object-oriented pipeline development.
  • Experience with workflow orchestration platforms such as Airflow or similar tools.
  • Strong understanding of data modeling concepts including fact/dimension modeling, normalization, and medallion architecture.
  • Experience with YAML-based configurations, CI/CD practices, and Git-based development workflows.

Requirements

Strongly Preferred:

  • Experience with enterprise data platforms, internal data tooling ecosystems, metadata/catalog solutions, secrets management tools, developer productivity platforms, and ETL orchestration frameworks.

Nice-to-Have:

  • Experience with Hive, Hadoop, Spark, or related big data technologies.

Benefits

·Competitive salary and performance-based bonuses.

·Comprehensive insurance plans.

·Collaborative and supportive work environment.

·Chance to learn and grow with a talented team.

·A positive and fun work environment.





More Info

Job Type:
Industry:
Employment Type:

Key Skills

enterprise data platforms

secrets management tools

ETL orchestration frameworks

developer productivity platforms

internal data tooling ecosystems

metadata catalog solutions

YAML-based configurations

object-oriented pipeline development

type hints

data classes

CI/CD practices

Git-based development workflows

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