Data Engineer

Prophecy Technologies

$100K — $140K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Proven ability to articulate and apply data strategy principles.
  • Experience in data extraction, pipeline creation, and data transformation.
  • Strong knowledge of current analytics trends and methodologies.
  • Familiarity with data modeling, including data warehouses and marts.
  • Expertise in relational database design and stored procedure development.
  • Proficient in writing code for data solutions and processes.

Responsibilities

  • Apply data strategy principles to address business challenges.
  • Extract data and create pipelines for effective data structuring.
  • Stay updated on analytics trends and ensure data quality through checks.
  • Analyze and contribute to the development of data models and structures.
  • Design logical and physical data models with attention to relational data.
  • Evaluate existing models for discrepancies and enhance data flows.
  • Identify and propose solutions for integration challenges in data systems.

Benefits

  • Opportunities for professional development and training.
  • Collaboration with interdisciplinary teams on impactful projects.
  • Engagement in innovative data governance initiatives.
Full Job Description
Role Overview:

This role focuses on comprehensive data management, from strategy and source identification to transformation, modeling, and governance. The Data Engineer will be responsible for developing data pipelines, designing data models, writing code for solutions, and ensuring data quality and integration, while also applying business acumen to solve complex problems.

Key Responsibilities:
  • Understands, articulates, and applies principles of defined data strategy to routine business problems.
  • Extracts data from identified databases and creates data pipelines to transform data into relevant structures.
  • Develops knowledge of current analytics trends and identifies suitable data sources, performing initial data quality checks.
  • Analyzes complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models.
  • Develops Logical Data Models and Physical Data Models, including data warehouse and data mart designs, defining relational tables, primary/foreign keys, and stored procedures.
  • Evaluates existing data models and physical databases for variances and discrepancies, and develops efficient data flows.
  • Analyzes data-related system integration challenges and proposes appropriate solutions.
  • Writes code to develop required solutions and application features, creates test cases, proofs of concept, tests code, and deploys software to production servers.
  • Contributes code documentation, maintains playbooks, and provides timely progress updates.
  • Translates business problems within one's discipline to data-related or mathematical solutions, identifying appropriate methods like analytics, big data analytics, or automation.
  • Provides recommendations to business stakeholders, develops business cases, translates business requirements into projects, and recommends new processes.
  • Establishes, modifies, and documents data governance projects and recommendations, implementing practices in partnership with stakeholders.
  • Interprets company and regulatory policies on data, educates others on data governance processes, and provides recommendations on needed updates.

Required Skills:
  • Understanding, articulating, and applying principles of defined data strategy.
  • Data extraction from identified databases, data pipeline development, and data transformation techniques.
  • Knowledge of current analytics trends.
  • Understanding of requirements prioritization and service level agreements, data source identification, and data quality validation.
  • Conceptual, logical, and physical data modeling, including data warehouse and data mart design.
  • Relational database design, primary and foreign key design, and stored procedure development.
  • Data flow development and data-related system integration analysis and solutioning.
  • Code development based on business, technical, and data requirements.
  • Test case creation, proof of concept development, software testing, and production deployment.
  • Code documentation and playbook maintenance.
  • Business problem translation into data-related or mathematical solutions, analytics, big data analytics, and automation.
  • Business stakeholder engagement, business case development, business requirements translation, and strategic project alignment.
  • Process improvement and recommendations.
  • Data governance implementation and documentation.
  • Regulatory and company policy interpretation, data governance education and training, and policy/practice/guideline recommendations.

Qualifications:
  • N/A

Preferred Skills:
  • N/A

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