Position : Lead ETL Developer
Location: Remote 100%
Duration: 6+ Months Contract
Client: Deloitte
Note:
- Extensive experience in SQL development
- Strong SQL background in Datawarehouse
- Hands-on expertise with Informatica PowerCenter or IICS
- Query tuning and optimization
- Proven ability to lead and develop applications, including designing, coding, and mentoring junior developers
- The candidate should be ready to take ownership of projects, drive technical solutions, and collaborate effectively with cross-functional teams.
- Redshift
Key Responsibilities:
ETL Development & Innovation: Architect, develop, and optimize sophisticated ETL workflows using Informatica PowerCenter and IICS to manage data extraction, transformation, and loading from diverse sources into Amazon Redshift and other platforms, incorporating real-time and near-real-time processing capabilities.
Cloud Data Integration & Orchestration: Lead the implementation of cloud-native data integration solutions using IICS, leveraging API-driven architectures to seamlessly connect on-premises, cloud, and hybrid ecosystems, ensuring scalability, resilience, and low-latency data flows.
Advanced Data Modeling: Design and maintain enterprise-grade logical and physical data models, incorporating advanced techniques like Data Vault or graph-based modeling, to support high-performance data warehousing, and analytics.
Data Warehousing Leadership: Spearhead the development and optimization of Amazon Redshift data structures, utilizing advanced features like Redshift Spectrum, workload management, and materialized views to handle petabyte-scale datasets with optimal performance.
Advanced Analytics : Conduct in-depth data profiling, cleansing, and analysis using Python and advanced analytics tools to uncover actionable insights, to enable predictive and prescriptive analytics.
Python-Driven Automation: Develop and maintain Python-based scripts and frameworks for data processing, ETL automation, and orchestration, leveraging libraries like pandas, PySpark, or Airflow to streamline workflows and enhance operational efficiency.
Performance Optimization & Cost Efficiency: Proactively monitor and optimize ETL processes, Redshift queries, Python scripts, and data pipelines using DevOps practices (e.g., CI/CD for data pipelines) to ensure high performance, cost efficiency, and reliability in cloud environments.
Cross-Functional Leadership & Innovation: Collaborate with data scientists, AI engineers, business stakeholders, and DevOps teams to translate complex business requirements into innovative data solutions, driving digital transformation and business value.
Data Governance & Ethics: Champion data governance, quality, and ethical data practices, ensuring compliance with regulations (e.g., GDPR, CCPA) and implementing advanced data lineage, auditing, and observability frameworks.
Documentation & Thought Leadership: Maintain comprehensive documentation of ETL processes, data models, Python scripts, and configurations while contributing to thought leadership by sharing best practices, mentoring teams, and presenting at industry forums.
Experience:
- 10-15 years of hands-on experience with Informatica PowerCenter for designing and implementing complex ETL workflows.
- 5+ years of experience with Informatica Intelligent Cloud Services (IICS) for cloud-based data integration and orchestration.
- 5-7 years of hands-on experience with Amazon Redshift, including advanced schema design, query optimization, and large-scale data management.
- Extensive experience (8+ years) in data modeling (conceptual, logical, and physical) for data warehousing, analytics solutions.
- 7+ years of experience as a Data Analyst, performing advanced data profiling, analysis, and reporting to support strategic decision-making.
- 5+ years of hands-on experience with Python for data processing, automation, and integration with ETL, data warehousing, and analytics platforms.
Technical Skills:
- Expert-level proficiency in Informatica PowerCenter and IICS for ETL and cloud-native data integration.
- Advanced SQL skills for querying, optimizing, and managing Amazon Redshift environments, including expertise in Redshift-specific features.
- Strong expertise in data modeling tools (e.g., ER/Studio, Erwin, or Data Vault) and advanced modeling techniques (e.g., star/snowflake schemas, graph-based models).
- Proficiency in Python for data manipulation, automation, and analytics (e.g., pandas, NumPy, PySpark, Airflow).
- Experience with data visualization and analytics platforms (e.g.,MSTR, Power BI) for delivering actionable insights.
- Familiarity with AWS cloud services (e.g., S3, Glue, Lambda, SageMaker) and DevOps tools (e.g., Jenkins, Git) for data pipeline automation.
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