Data Engineer

 Posted a day ago
     
⭐ 5-10 years experience
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AI Summary

The role involves cleansing, transforming, and consolidating historical workforce and financial data for a legal services client. The engineer will develop automated conversion processes and collaborate with stakeholders to translate business requirements into scalable data solutions.

About Kaizen Analytix

Kaizen Analytix is a technology and analytics consulting firm specializing in data, AI, cloud, and digital transformation solutions. We help organizations modernize their data ecosystems, optimize business processes, and accelerate decision-making through innovative technology solutions and deep industry expertise. Our consultants partner closely with clients to deliver measurable business outcomes through data-driven innovation, scalable architecture, and operational excellence.

Position Overview

Kaizen Analytix is seeking an experienced Data Engineer to support a critical data conversion and migration initiative for a leading legal services client. This role will be responsible for cleansing, transforming, consolidating, and validating historical workforce and financial system data while developing automated data conversion processes that improve quality, consistency, and efficiency.

The ideal candidate combines strong technical data engineering expertise with the ability to work directly with business stakeholders to translate business requirements into scalable data solutions. This is a highly visible client-facing role requiring excellent communication skills, strong attention to detail, and the ability to operate independently in a fast-paced environment.

Key Responsibilities

  • Analyze and consolidate historical workforce, FTE, and timekeeper data from multiple source systems.
  • Design and develop automated data conversion and transformation processes to reduce manual effort and improve data quality.
  • Extract data from APIs, databases, flat files, and other structured and unstructured sources.
  • Perform data cleansing, standardization, validation, and enrichment activities to ensure data integrity.
  • Transform and map source data to align with target system requirements and reporting standards.
  • Produce standardized output files and datasets that conform to the target application's native data model.
  • Partner with business stakeholders to gather requirements and translate business needs into technical data solutions.
  • Conduct data quality assessments, reconciliation, and validation activities throughout the migration lifecycle.
  • Support testing, dry-run conversions, and production migration activities.
  • Troubleshoot data issues and implement corrective actions as needed.
  • Document data mappings, transformation rules, conversion logic, and validation procedures.
  • Collaborate with project managers, business analysts, and client stakeholders to ensure successful project delivery.

Required Qualifications

  • 5+ years of professional experience in Data Engineering, ETL Development, Data Integration, or related fields.
  • Strong experience extracting, transforming, and loading data from multiple data sources.
  • Experience working with relational databases and writing complex SQL queries.
  • Proven ability to cleanse, standardize, and reconcile large datasets.
  • Experience developing automated data transformation and migration solutions.
  • Strong analytical and problem-solving skills.
  • Ability to work independently with minimal supervision.
  • Excellent verbal and written communication skills.
  • Experience working directly with business stakeholders and translating business requirements into technical solutions.
  • Strong understanding of data quality, governance, and validation best practices.

Preferred Qualifications

  • Experience with Elite 3E or similar legal, professional services, ERP, or financial management systems.
  • Prior experience supporting data migration, system conversion, or ERP implementation projects.
  • Familiarity with data integration tools, APIs, and modern cloud-based data platforms.
  • Experience supporting financial, workforce, or operational data conversion initiatives.

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