Data Engineering Team Lead
Austin, TX, US
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We are looking for a highly skilled Data Engineering Team Lead with a deep background in big data architectures and a proven track record of leading high-performing technical teams. You should be passionate about extreme performance and excited by the challenge of managing massive data streams. Your success will be measured by your ability to scale the engineering organization, design robust data quality frameworks, and deliver the infrastructure required for advanced machine learning feature serving. This is a full-time position based in Austin, TX, or New York, NY What will you do at Smadex? You will lead our core Data Engineering group, reporting directly to the Chief Data Officer . You will be the architect and leader for a collaborative group of engineers responsible for enabling complex data to be available in our real-time bidding platform for Machine Learning models. As the leader, you will oversee the formation and growth of two specialized sub-teams: Data Quality and Feature Engineering. We foster a fast-paced environment where autonomy is valued, and you will provide the platform for your team to solve extreme engineering challenges while growing their careers. You will lead the strategic expansion of our data capabilities, managing the end-to-end lifecycle of our data pipelines. You will be responsible for building out two distinct sub-teams: Data Quality Team: Focused on building automated testing, observability, and validation frameworks to ensure our massive data ingestion is accurate and reliable. Feature Engineering Team: Focused on bridging the gap between raw data and ML inference, building the "Feature Store" and Spark pipelines that feed our real-time bidding models. You will define the technical roadmap, mentor senior and junior engineers, and ensure operational excellence across our distributed systems.
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What you’ll work on
Full postingYou will lead our core Data Engineering group, reporting directly to the Chief Data Officer .
You will lead the strategic expansion of our data capabilities, managing the end-to-end lifecycle of our data pipelines.
You will define the technical roadmap, mentor senior and junior engineers, and ensure operational excellence across our distributed systems.
From the employer’s posting
We are looking for a highly skilled Data Engineering Team Lead with a deep background in big data architectures and a proven track record of leading high-performing technical teams. You should be passionate about extreme performance and excited by the challenge of managing massive data streams. Your success will be measured by your ability to scale the engineering organization, design robust data quality frameworks, and deliver the infrastructure required for advanced machine learning feature serving. This is a full-time position based in Austin, TX, or New York, NY What will you do at Smadex? You will lead our core Data Engineering group, reporting directly to the Chief Data Officer . You will be the architect and leader for a collaborative group of engineers responsible for enabling complex data to be available in our real-time bidding platform for Machine Learning models. As the leader, you will oversee the formation and growth of two specialized sub-teams: Data Quality and Feature Engineering. We foster a fast-paced environment where autonomy is valued, and you will provide the platform for your team to solve extreme engineering challenges while growing their careers. You will lead the strategic expansion of our data capabilities, managing the end-to-end lifecycle of our data pipelines. You will be responsible for building out two distinct sub-teams: Data Quality Team: Focused on building automated testing, observability, and validation frameworks to ensure our massive data ingestion is accurate and reliable. Feature Engineering Team: Focused on bridging the gap between raw data and ML inference, building the "Feature Store" and Spark pipelines that feed our real-time bidding models. You will define the technical roadmap, mentor senior and junior engineers, and ensure operational excellence across our distributed systems.
Tools in this posting
- Spark
Source — Tool mentions in context
We are looking for a highly skilled Data Engineering Team Lead with a deep background in big data architectures and a proven track record of leading high-performing technical teams. You should be passionate about extreme performance and excited by the challenge of managing massive data streams. Your success will be measured by your ability to scale the engineering organization, design robust data quality frameworks, and deliver the infrastructure required for advanced machine learning feature serving. This is a full-time position based in Austin, TX, or New York, NY What will you do at Smadex? You will lead our core Data Engineering group, reporting directly to the Chief Data Officer . You will be the architect and leader for a collaborative group of engineers responsible for enabling complex data to be available in our real-time bidding platform for Machine Learning models. As the leader, you will oversee the formation and growth of two specialized sub-teams: Data Quality and Feature Engineering. We foster a fast-paced environment where autonomy is valued, and you will provide the platform for your team to solve extreme engineering challenges while growing their careers. You will lead the strategic expansion of our data capabilities, managing the end-to-end lifecycle of our data pipelines. You will be responsible for building out two distinct sub-teams: Data Quality Team: Focused on building automated testing, observability, and validation frameworks to ensure our massive data ingestion is accurate and reliable. Feature Engineering Team: Focused on bridging the gap between raw data and ML inference, building the "Feature Store" and Spark pipelines that feed our real-time bidding models. You will define the technical roadmap, mentor senior and junior engineers, and ensure operational excellence across our distributed systems.
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Austin, TX, US
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- Status in our records
- Active
- First seen by us
- Sep 8, 2026
- Recorded sightings
- 89
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Sep 4, 2026
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