Julian is a highly skilled Data Engineer with expertise in API, ETL, Data Lake, and a comprehensive technology stack encompassing Power BI, BigQuery, MySQL, and XML. He is proficient in designing, creating, and deploying complex data pipelines, connecting BI tools to data sources, applying best practices in data warehousing, and leading and coordinating data teams. Julian has created and deployed 100+ data pipelines and batch jobs in Python and Spark, extracting raw data from API’s MySQL data sources and storing them in the staging and landing zone (CSV, JSON, and XML files). He has experience designing and architecting data solutions in cloud and on-premises environments. He has utilized multipurpose and job compute clusters (ephemeral) and incorporated external Delta Tables in S3. Julian has applied good practices in DW and columnar databases, including clustering, partitioning, compression, materialized views, and denormalization, and has migrated the previous Data Warehouse from BigQuery to Redshift, implementing Dimension Model Type 2 in Redshift. He has provided technical guidelines for data modeling, analytics, and big data and participated in RFI/RFP processes.

Akinola Ogunnaike is a Data Governance Analyst with a decade of experience and has certifications in Data Management and Governance, including Informatica's Data Governance and Privacy. He specializes in leading data governance initiatives, identifying critical data elements, and developing data policies to ensure data adoption and quality across organizations. Akinola is proficient in Data Management, Agile Methodologies, and serves as a subject matter expert in Collibra and Informatica. He designs and implements data strategies aligned with business objectives, emphasizing accurate, complete, and timely data for informed decision-making. Akinola has a proven track record in leading enterprise data governance programs, developing strategies, forming Data Governance Councils, and managing key information assets through technology platforms.

Arpit Gautam is an experienced Informatica Data Engineer with 8 years of expertise in data analysis, consulting, data modeling, and strategy execution. He specializes in developing data pipelines using Informatica PowerCenter and IDMC/IICS (CAI, CDI) across SDLC life cycle models like Waterfall and Agile. Arpit excels in sourcing, prototyping datasets, and aligning data outcomes with business strategies. His skills include ETL development, SQL coding, UAT, and Unit testing, with proficiency in IICS, Informatica PowerCenter, Redshift, SQL Server, Postgres, Oracle, DB2, S3, ITSM, and ServiceNow for Incident and Change Management. Arpit is adept with automation tools like Control-M and Autosys, and has experience in PL/SQL, data warehousing, HP ALM for ETL code testing, Python (NumPy, Pandas), AWS EC2, Unix environments, and Tableau. He ensures seamless data transfers to dashboards and collaborates effectively with teams for sales reporting and customer payouts.

Diana is an accomplished Data Analyst with a wealth of experience in shaping organizational strategies and optimizing processes through data-driven insights. She has played a pivotal role in defining and executing the company's payment strategy, leading a successful migration to microservices and substantially reducing product-related issues. Diana is proficient in tools like Tableau, Pentaho, and AWS, Microsoft Excel, Data Aggregation, Data Analytics, Data Center Virtualization, Data Design, Data Segmentation, Data Validation, tableau server administration, Data Cleaning, Snowflake, and Python, with her expertise extending to agile team management, strategic visioning, and cross-functional collaboration. She has utilized SQL and visualization tools to query diverse data sources, automated reporting processes, and provided crucial insights for decision-making. Her achievements include being recognized as the best analyst of the year, leading successful cloud migrations, establishing data governance, and implementing innovative BI models.

Juan is a Data Architect with expertise in Docker, Machine Learning, Jenkins, and Terraform technologies. He has led transformative initiatives, including migrating on-premises data to an AWS data lake, significantly enhancing data management and accessibility. Juan has successfully constructed a lakehouse solution using various AWS services, including S3, Redshift, Step Functions, Event Bridge, Kinesis, Glue, and Athena. He has implemented Python automation to update warehouse data, optimizing data mart creation to enhance the sources and speed of the dashboards. Juan has demonstrated proficiency in various tools and platforms, optimizing data migration, machine learning, and DAG deployments. Juan is an invaluable Data Architect with experience in orchestrating data processes across various AWS services and enhancing report generation speed and efficiency. His skills include implementing machine learning pipelines for cancel rate reduction, effectively leveraging AWS SageMaker, and improving operational efficiency. His keen eye for data organization and supply chain operations, devising strategic sales plans, and leading high-performing teams underscores his multifaceted skill set.

Gustavo is a result-driven cloud data engineer with over 4+ years of experience developing an organization’s Big Data foundation by operating the end-to-end life cycles of robust data pipelines utilizing the Data Quality and Data Lineage. He has strong knowledge in tech piles like SQL, Python, Spark, Databricks, Airflow, and cloud platforms like Azure, AWS, and GCP. In his most recent role, Gustavo has contributed to creating consolidated data from various sources, supporting the migration of Delta Tables, and implementing data mesh architecture to build data-driven solutions. He has demonstrated expertise in building, implementing, and maintaining innovative features and products in software engineering, data engineering, data analysis, and data science for large companies and multinationals.