Data Engineer III

Posted 4 Days Ago
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Philippines
Mid level
Hardware • Machine Learning • Software
The Role
The Data Engineer III will develop and maintain data pipelines, oversee data storage solutions, ensure data quality, and mentor junior engineers, while collaborating with cross-functional teams to enhance data-driven decision-making.
Summary Generated by Built In

We are DemandScience, a global company which never stops innovating in our mission to provide the healthiest and most predictive global B2B data and intelligence for our customers. Our clients include sales and marketing professionals at global companies. Excellent execution is in our DNA. We provide innovative AI-analytics merged with enriched data to identify your next in-market prospects and customers at scale.


Position Summary:

We are currently seeking a Data Engineer to join our team and deliver high-quality data engineering solutions while maintaining existing systems. The ideal candidate should strive to provide a best-in-class experience for our data consumers and contribute to the design, implementation, testing, and maintenance of data stores.

The candidate must ensure on-time delivery of high-quality data while adhering to best practices. They should possess a passion for continuous learning and staying current with the latest technologies.

The candidate should lead and execute complex data engineering projects and initiatives, design and implement data pipelines, manage data infrastructure, and drive data architecture decisions to support data-driven decision-making and business analytics, provide technical expertise, mentor junior data engineers, and collaborate with cross-functional teams to deliver innovative and scalable data solutions.


Essential Job Functions “What You’ll Do”:

  • Contributing to the design, development, and maintenance of robust data pipelines, focusing on ELT and ETLT design patterns. Taking ownership of at least one project pillar during development.
  • Collaborating with engineering leadership to define data architecture principles and guidelines. Bringing multiple approaches for solving a problem, along with their pros and cons, into architecture meetings.
  • Overseeing the implementation and management of data storage solutions, data lakes, and data warehouses, as well as designing and developing data models and database schemas to support efficient data querying and reporting, ensuring data storage and retrieval mechanisms meet performance and scalability requirements.
  • Overseeing implementing data security measures to protect sensitive information and ensure compliance with data privacy regulations.
  • Lead in integrating data from various sources, including databases, APIs, and external data feeds.
  • Oversee the implementation of data validation and quality checks to identify and handle data anomalies.
  • Lead in optimizing data storage and retrieval mechanisms for improved performance, database performance optimization and indexing tasks, in data cleansing, preprocessing, and transformation to maintain data accuracy and consistency.
  • Identify the critical details and prioritize incremental delivery.
  • Adhering to data governance practices and guidelines for data access and usage.
  • Oversee monitoring data pipelines and database performance, identifying and resolving performance bottlenecks, and contributing to data processing and storage optimization efforts.
  • Provide input and contribute to monitoring & alerting requirements and implementation
  • Help develop & maintain your team’s CI/CD needs, and automate data processing tasks and workflows to improve efficiency and reduce manual effort.
  • Share and implement ideas to help our teams move quickly.
  • Working closely with data analysts, data scientists, and other stakeholders to understand data requirements and deliver effective data solutions.
  • Communicating technical concepts and findings to non-technical stakeholders when required.
  • Experience in evaluating and implementing appropriate data engineering tools and technologies.
  • Strong interest in problem-solving, and strong analytical skills, learning and applying appropriate data engineering tools and technologies.
  • Contributing to maintaining documentation of data pipelines, schemas, and processes.
  • Working closely with the stakeholders to understand data requirements and deliver effective data solutions. 

 

Essential Qualifications “What You’ll Need”: 

  • Bachelor’s degree in computer science, Information Systems or a related technical discipline.
  • 5 - 7 years of production hands-on experience in data pipeline development, data integration, and data warehouse management, either in industry or as part of an academic program.
  • 5 - 7 years of production experience in enterprise data warehouses and data lakes.
  • 5+ years of production experience in the B2B space
  • 3+ years of experience as a Senior Engineer or similar role involving team and project leadership.
  • AWS hands-on experience.
  • Strong proficiency in programming languages commonly used in data engineering, such as Python, Java, Scala, SQL / PLSQL
  • Extensive production experience with data engineering tools and frameworks, such as Apache Spark, Apache Kafka, Apache Airflow, or similar technologies.
  • Deep understanding of database systems, either relational (e.g., PostgreSQL, MySQL) or NoSQL (e.g., MongoDB, Cassandra)
  • Knowledge of data modelling concepts and database design principles. 
  • Knowledge of data security, data privacy, and data governance best practices.
  • Extensive experience with DevOps activities in CI/CD.
  • Extensive experience with monitoring & logging technologies (Splunk, New Relic…)
  • Strong analytical and problem-solving skills, with attention to detail.
  • Excellent communication, both written and verbal, and interpersonal skills, with the ability to collaborate effectively in a team environment.
  • Proven ability to mentor more junior engineers.
  • Proven ability to convey ideas to a broad audience of different specializations.
  • Substantial ownership and focus on long-term usability and extensibility.
  • Collaborative attitude, team player, friendly, w/ passion and flexibility to learn new tools and skillsets.
  • Work toward goals, meet deadlines, and contribute positively to the team environment.
  • Track record of delivering high-quality data or software projects, either in industry or as part of an academic program.
  • A continuous learning mindset to stay updated with the latest trends and advancements in data engineering.
  • Skilled in the use of Microsoft Office products

 

THE GOOD STUFF!

We embrace diversity and inclusion and encourage our amazing team members at DemandScience to bring their authentic, fun selves to work every day. We offer a culture of innovation, mutual respect, support, and transparency.  The competitive and comprehensive benefits our team members enjoy are designed to ensure you and your family members are healthy. Check this out!

  • Paid time off
  • Medical provided through HMO
  • Life Insurance
  • Peer-Appreciation Program
  • Employee Referral Program
  • A fast-paced, innovative culture with an open and collaborative environment, where you can make an impact.
  • Join a great organization that cares about employees!

DemandScience is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

#LI-Remote

Find out more at https://demandscience.com/careers/#join-the-team

Top Skills

Apache Airflow
Apache Kafka
Spark
AWS
Cassandra
Java
MongoDB
MySQL
New Relic
Plsql
Postgres
Python
Scala
Splunk
SQL
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The Company
Greater Boston
1,141 Employees
Year Founded: 2012

What We Do

DemandScience is the premier B2B demand generation company accelerating global growth for our clients. The DemandScience intelligence platform empowers B2B organizations to swiftly identify the right accounts and target in-market buyers with precision. By combining groundbreaking technologies, machine learning and data science innovation, the company ensures timely delivery of accurate data, intelligence, and insights, adding value to the end-to-end journey from initial engagement to conversion. Founded in 2012, DemandScience provides 1,500 global customers with superior marketing solutions, B2B data, and leads. With a team of 600+ employees across operations in seven countries, DemandScience is certified as a Great Place To Work, named #5 on Fortune Magazine’s 2022 list of the Best Workplaces in Advertising & Marketing, and one of only 143 companies in history to be named to the Inc. 5000 for 10 consecutive years. For further insights on why DemandScience stands at the forefront of transformative demand generation

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