HajaData Meetup: Operationalizing & Data Quality

​As organizations become increasingly data-driven, the challenge is no longer just collecting data - it’s building reliable systems that teams can trust and operate in real time. In this meetup, we’ll explore how modern data platforms evolve from scalable, high-availability pipelines to mature data quality practices that enable organizations to move faster with confidence.

​Yair Ofek will start by sharing how to operationalize data by bridging offline and online systems through self-service, high-availability pipelines built for real-time applications. Then, Valter Fernandes will take us on a journey toward data quality maturity - from foundational standards and ownership to observability, governance, and autonomous processes that turn trusted data into a competitive advantage.

​Join us for an evening of data engineering, platform thinking, and operational excellence.

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​Agenda:

​18:00 - 18:30 - Mingling, drinks, and snacks

​18:30 - 18:45 - Opening remarks

​18:45 - 19:15 - Operationalizing Data – Building High-Availability Pipelines from Offline to Online - Yair Ofek, Senior Data Platform Engineer at Riskified

​19:15 - 19:45 - A Journey to the Peak of Data Quality - Valter Fernandes, Engineering Leader

​19:45 - 20:30 - More drinks and mingling

​The talks will be delivered in English.

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​// Operationalizing Data – Building High-Availability Pipelines from Offline to Online - Yair Ofek, Senior Data Platform Engineer at Riskified

​Modern data engineering faces a significant challenge: bridging the gap between high-capacity offline storage and the high-performance online systems required for real-time applications. Whether serving data science models in real time or enabling engineering teams to patch data at scale, this talk provides a clear roadmap for building a self-service platform that automates the heavy lifting of data synchronization.

​We’ll explore the fundamental differences between offline “lake” systems and high-throughput online databases, and why traditional pipelines are just not a good enough solution for your production. We’ll also cover how to choose the right architecture for your goals. By the end, you’ll understand how an API-driven, automated infrastructure empowers developers to independently trigger and manage data flows, ensuring critical insights are always available exactly where and when they’re needed.

​About the speaker:
Yair Ofek is a Senior Big Data Engineer at Riskified with over a decade of experience across the data lifecycle. Since joining Riskified in 2017, he has held roles ranging from Research Analyst to Engineering Lead for Data Integrations.
Currently based in Lisbon, Yair focuses on building the robust infrastructure required to handle Big Data at scale. He is passionate about bridging the gap between raw data and production-grade engineering, ensuring that complex systems remain both reliable and impactful.

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​// A Journey to the Peak of Data Quality - Valter Fernandes, Engineering Leader

​The lifecycle and roadmap of Data Quality for a company looks a lot like slowly and steadily climbing a very tall mountain. It requires training, studying, adapting and preparing for the challenge ahead of us. How high you can reach is a reflection of the maturity of the organization’s processes, technology, and culture. And, skipping or rushing steps often leads to operational friction, unreliable insights and team fatigue.

During this conversation, on our way to the peak, we'll climb our way towards and through 3 "Base Camps":
- Base Camp 1: “Data Sanity” - The path begins with essential foundations like establishing standards, validating data, and creating ownership.
- Base Camp 2: “Data Reconciliation” and “Process Monitorization” - As teams progress the climb, it comes the time to introduce reconciliation processes, monitoring, observability, governance, and automation. This leads to gradually building confidence and trust in their data and its ecosystem.
- Base Camp 3: “Intelligence” - With trusted and high quality data comes the possibility to create visualisation and tooling such as predictive analytics or, more recently, AI.

This journey to the Peak of Data Quality is ultimately a journey or maturity from reactive problem-solving to proactive and autonomous processes that build trust into your data and finally unlock usages for it that turn it into business value and even a competitive advantage.

​About the speaker:
Valter Fernandes is an engineering leader with extensive experience scaling software, data, and platform engineering organizations across different enterprise environments. He has led international distributed teams of people and helped companies navigate high-growth and transformation phases through organizational redesign, process optimization, and technology modernization.
His background combines hands-on technical expertise in software and data engineering with strategic leadership in areas such as SDLC improvement, CI/CD, data platforms, cloud infrastructure, and operational excellence. Throughout his career, he has contributed to turning early-stage concepts into production-grade products while building high-performing engineering cultures focused on trust, ownership, and delivery quality.

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​See you soon!