Data Engineer

Compunnel

$100K — $120K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4-8 years of data engineering experience including data modeling and SQL expertise.
  • Recent background in banking, financial services, or capital markets.
  • Familiarity with REST APIs and GraphQL.
  • Proficient in ETL development and data pipeline orchestration.
  • Hands-on experience utilizing Azure Data Factory, Azure Data Lake, and Azure Databricks.
  • Knowledgeable in Spark, Python, or Scala for data processing.
  • Awareness of data governance, security, and compliance practices.
  • Capable of independent and collaborative work with strong problem-solving skills.

Responsibilities

  • Design, develop, and optimize data models and schemas aligned with business needs.
  • Develop and maintain efficient ETL pipelines using Spark and Databricks.
  • Write complex SQL queries for data extraction and processing.
  • Collaborate with analytics and business teams to deliver data solutions.
  • Build scalable data solutions using Azure Data services.
  • Ensure data quality, governance, and security across processes.
  • Monitor and optimize data pipelines for performance and availability.
  • Document data workflow and participate in code reviews.

Benefits

  • Work with cutting-edge technology in data engineering.
  • Opportunity to impact data solutions in the banking and finance sectors.
  • Gain experience in a fast-paced, collaborative environment.
  • Access to professional development and training opportunities.
Full Job Description
Job Summary

The role involves designing, developing, and optimizing data models, ETL pipelines, and scalable data solutions using Azure Data Services, Spark, and Databricks. The position requires strong experience in data engineering, SQL, and cloud-based data platforms, with a focus on supporting business requirements, ensuring data quality, and maintaining high-performance data workflows.

Key Responsibilities

  • Design, develop, and optimize data models and schemas aligned with business needs.
  • Develop, implement, and maintain efficient ETL pipelines using Spark, Databricks, and related tools.
  • Write complex SQL queries, stored procedures, and functions for data extraction, transformation, and loading.
  • Collaborate with analytics and business teams to gather requirements and deliver data solutions.
  • Build scalable data solutions using Azure Data Lake, Azure Data Factory, and Azure Databricks.
  • Ensure data quality, governance, and security across all data processes.
  • Monitor, optimize, and troubleshoot data pipelines to ensure performance and availability.
  • Document data architecture, workflows, and procedures, and participate in code reviews and best-practice development.


Required Qualifications

  • Overall, 9+ years of experience.
  • 6+ years of experience in data engineering with strong expertise in data modeling and SQL.
  • Should have recent experience in the banking/financial services/capital markets domain
  • Proven experience with ETL development and data pipeline orchestration.
  • Hands-on experience with Azure Data Factory, Azure Data Lake, and Azure Databricks.
  • Strong knowledge of Spark, Python, or Scala for data processing.
  • Familiarity with data governance, security, and compliance best practices.
  • Strong problem-solving skills and attention to detail.
  • Ability to work independently and collaboratively within a team.
  • Bachelor's degree in Computer Science, Information Technology, or a related field.


Preferred Qualifications

  • Certifications in Azure data services or Databricks.
  • Experience with BI tools and reporting.
  • Knowledge of other cloud platforms.


Certifications

  • Certifications in Azure Data Services or Databricks

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