To Apply for this Job Click Here Job Title: Data Engineer Location Requirements: Hybrid Job Type: Contract Role Overview: You will design, build, and support scalable data solutions in a high-volume enterprise environment. Collaborate with Data Science, Analytics, Product, Engineering, Architecture, Security, and business teams to deliver trusted data for operational reporting, advanced analytics, machine learning, and strategic decision-making. Contribute across the data lifecycle, from ingestion and transformation to storage, quality, monitoring, and consumption. Responsibilities: • Design, develop, test, deploy, and maintain scalable batch and real-time data pipelines. • Integrate structured, semi-structured, and unstructured data from internal and external sources. • Build reusable data products, services, and frameworks for analytics, reporting, and machine learning. • Develop and optimize ETL and ELT processes using modern cloud data technologies. • Design and maintain data models supporting business intelligence, operational reporting, and analytics. • Partner with stakeholders to translate data requirements into reliable, maintainable solutions. • Collaborate with Data Scientists, Analysts, Software Engineers, and Product teams to ensure data accessibility, accuracy, and fitness for purpose. • Implement automated data-quality checks, validation rules, reconciliation processes, and monitoring. • Diagnose and resolve pipeline failures, performance issues, data inconsistencies, and incidents. • Optimize data-processing workloads for performance, scalability, reliability, and cost efficiency. • Apply data governance, security, privacy, retention, and access-control standards throughout the data lifecycle. • Maintain technical documentation, including data mappings, lineage, architecture, operational procedures, and support requirements. • Build and support continuous integration and delivery processes for data pipelines and infrastructure. • Participate in architecture reviews and recommend solutions that balance business needs, technical quality, cost, and delivery timelines. • Contribute to Agile ceremonies such as backlog refinement, sprint planning, daily stand-ups, reviews, and retrospectives. • Coordinate cross-team integrations, releases, and dependencies. • Support production systems and participate in incident-response activities as needed. • Research emerging data technologies and recommend platform and process improvements. Required Qualifications: • Three or more years of experience in data engineering, software engineering, or a related technical role. • Strong proficiency in SQL and at least one programming language used for data engineering, such as Python, Java, or Scala. • Experience designing and maintaining ETL or ELT pipelines in an enterprise environment. • Experience working with relational databases, data warehouses, data lakes, and/or lakehouse platforms. • Knowledge of dimensional modeling, data architecture, and data-integration patterns. • Experience with cloud-based data platforms and services. • Familiarity with orchestration, version control, automated testing, and CI/CD tools. • Understanding of data-quality, governance, security, and privacy principles. • Experience working in an Agile product-development environment. • Strong analytical, troubleshooting, communication, and collaboration skills. • Ability to manage competing priorities and deliver dependable solutions in a fast-paced environment. Preferred Qualifications · Experience working with retail, e-commerce, customer, loyalty, merchandising, supply chain, inventory, pricing, payment, or fulfillment data. · Experience with Microsoft Azure, Google Cloud Platform, or Amazon Web Services. · Experience with platforms and technologies such as Databricks, Snowflake, BigQuery, Redshift, Spark, Kafka, or similar tools. · Familiarity with orchestration tools such as Airflow, Azure Data Factory, or comparable technologies. · Experience building streaming or event-driven data pipelines. · Knowledge of infrastructure as code, containerization, and DevOps or DataOps practices. · Experience with data catalogs, metadata management, lineage, master data management, or governance platforms. · Familiarity with business-intelligence and visualization tools such as Power BI, Tableau, or Looker. · Experience supporting machine-learning or artificial-intelligence data workflows. · Knowledge of observability practices for monitoring pipeline health, data freshness, performance, and reliability. To Apply for this Job Click Here Equal Employment Opportunity Statement Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.