hotskills.tech

About Job

The Role This role provides the opportunity to work at the intersection of data engineering and analytics, making a tangible impact on business strategy and operations. You will work with cutting-edge tools, collaborate with diverse teams, and help shape the data strategy across the organization while solving challenging, high-impact problems. Responsibilities: Data Engineering Pipeline Management: • Design, develop, and maintain scalable ETL pipelines for ingestion, transformation, and integration of structured and unstructured • Optimize SQL queries, stored procedures, triggers, and automation scripts to handle large, complex datasets • Ensure data quality, integrity, and consistency across multiple systems and • Implement error handling, logging, monitoring, and alerting mechanisms for reliable production • Collaborate with DevOps and engineering teams to deploy data workflows and ensure seamless integration with production Data Modeling Governance: • Design and implement relational, dimensional, and Master Data Management (MDM) models tailored to finance, operational, and enterprise • Develop detailed entity-relationship (ER) diagrams and define indexing, partitioning, and normalization strategies for optimal • Establish and enforce data governance, validation rules, standardization policies, and documentation for maintainable • Implement slowly changing dimensions (SCDs) and hierarchical structures to support evolving business requirements. Analytics Business Impact: • Translate raw operational, financial, and transactional data into actionable insights that drive revenue growth, cost reduction, and process optimization. • Develop predictive and prescriptive models for forecasting, anomaly detection, risk assessment, and decision support. • Validate, monitor, and improve model accuracy, fairness, explainability, and operational • Quantify the business impact of data initiatives and communicate actionable recommendations to stakeholders. Collaboration Communication: • Partner with business intelligence, analytics, finance, operations, and product teams to identify opportunities for data-driven • Produce dashboards, reports, and narratives that clearly communicate insights to non-technical stakeholders. • Translate complex technical concepts into business-relevant • Document data models, transformation logic, metadata, and processes for cross-team knowledge sharing. Data Quality Responsible AI: • Profile and monitor data to detect inconsistencies, gaps, and anomalies, implementing corrections as • Enforce metadata standards, data lineage, and data security, privacy, and compliance best practices. • Ensure ethical use of AI/ML models by managing bias, transparency, and operational • Maintain rigorous documentation of assumptions, limitations, and model performance for auditing and ... Other Required Skills Experience: • Strong SQL programming (PL/SQL, T-SQL) with hands-on experience in relational databases such as Oracle, SQL Server, and • Expertise in data modeling (relational, dimensional, MDM) and database design best • Proven experience with ETL tools such as Informatica, Talend, or • Solid understanding of data governance, lineage, and quality • Experience in performance tuning, indexing, partitioning, and optimization for large • Strong problem-solving, analytical, and critical-thinking • Ability to work effectively in cross-functional teams and communicate complex technical concepts to business stakeholders. Preferred Qualifications: • Experience in financial data management, enterprise MDM projects, or similar • Familiarity with reporting and BI tools such as Power BI, SSRS, or • Knowledge of scripting and automation using Python, Shell, or similar • Experience deploying predictive or prescriptive models in production • Familiarity with cloud platforms (AWS, Azure, GCP) and modern data ... Profile ... job perk: Posted At: 16 hours ago, job perk: Schedule Type: Full-time, job perk: Qualifications: No degree mentioned