Role Description CTG is seeking a GCP Data Engineer / Migration Lead to lead Hadoop-to-Google Cloud migrations and modernization initiatives. The role involves designing, building, and maintaining scalable batch and real-time data pipelines, managing cloud-based data platforms, and leading a team through discovery, analysis, and migration workshops. - Lead migration of databases and data objects (tables, views, procedures, triggers) from Hadoop to GCP. - Build and manage pipelines using: - DataProc - DataFlow - BigQuery - BigTable - Cloud Spanner - CloudSQL - AlloyDB - APIs - Implement CDC, bulk, and file-based data replication. - Analyze application dependencies, non-functional requirements, and modernization roadmaps. - Prepare project plans, WBS, RACI, effort estimates, and lead team adoption of tools and best practices. - Orchestrate pipelines via Cloud Composer (Airflow) and Cloud Scheduler. Qualifications - Hands-on experience in Hadoop, Spark (Python/Scala), Airflow, dbt, and GCP data services. - Expertise in batch & real-time pipelines, data warehouses, and data lakes. - Strong leadership and team mentoring experience in cloud migration projects. - Proven ability to analyze technical & non-functional requirements. - Education: Bachelor’s or Master’s in Computer Science, IT, or related field, or equivalent experience. - Google Cloud certifications are a plus. - Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required. Benefits - The expected base salary for this position ranges from $119,000 to $125,000. - Salary offers are based on a wide range of factors including relevant skills, training, experience, education, market factors, and where applicable, licensure or certifications obtained. - In addition to salary, a competitive benefit package is also offered. Company Description CTG, a Cegeka company, is at the forefront of digital transformation, providing IT and business solutions that accelerate project momentum and deliver desired value. Over nearly 60 years, we have earned a reputation as a faster and more reliable, results-driven partner. Our vision is to be an indispensable partner to our clients and the preferred career destination for digital and technology experts. CTG leverages the expertise of over 9,000 team members in 19 countries to provide innovative solutions. Our culture is a direct result of the people who work at CTG, the values we hold, and the actions we take. In other words, our people define our culture. It's a living, breathing thing that is renewed every day through the ways we engage with each other, our clients, and our communities. Part of our mission is to cultivate a workplace that attracts and develops the best people. CTG will consider for employment all qualified applicants including those with criminal histories in a manner consistent with the requirements of all applicable local, state, and federal laws. CTG is an Equal Opportunity Employer. CTG will assure equal opportunity and consideration to all applicants and employees in recruitment, selection, placement, training, benefits, compensation, promotion, transfer, and release of individuals without regard to race, creed, religion, color, national origin, sex, sexual orientation, gender identity and gender expression, age, disability, marital or veteran status, citizenship status, or any other discriminatory factors as required by law. CTG is fully committed to promoting employment opportunities for members of protected classes.

Data Engineer Department: Technology Employment Type: Full Time Location: Chicago, IL Description We are seeking a motivated, self-directed, and technically outstanding data engineer to join our team of engineers responsible for designing, building, and maintaining the data pipelines that are critical to our business. The ideal candidate enjoys optimizing data systems and building them from the ground up. You should be comfortable supporting our developers, data analysts, and traders to ensure data delivery is consistent, high-quality, and secure. Hours - Hours for this position will be 5:30 AM CST to 2:30 initially and are expected to shift to the evening at a later date. Location - Our office is in Chicago, and a Chicago based employee is preferred. However, due to the non-standard working hours required, we will consider a remote employee with the right experience and skillset What You'll Do - Pipeline Development: Design, construct, and manage scalable data pipelines. - Architecture: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources. - Optimization: Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability. - Data Modeling: Create and maintain optimal data pipeline architecture and database schemas - Gather requirements, design solutions, iterate on implementations with peers and business partners, participate in code reviews, and deliver products in a timely manner - Troubleshoot and solve the most complex problems escalated by support staff, developers, or traders - Provide insights on and help prioritize tasks to optimize, modernize, and simplify our system on your own initiative, as well as ways to improve usability and scalability - Document the requirements and usage of tools and systems - Keep abreast of emerging technologies, new language features, and new APIs or tools What We're Looking For - Have 3+ years of experience in a data engineering role - Languages: Expert-level SQL and proficiency in Python, C#/.Net, or some other programming language - Broad technical knowledge with strong conceptual understanding of Linux sysadmin (bash) - Be organized, self-directed, and dependable. Be able to manage your own workload and provide reasonable estimates for task completion - Have superb analytical and problem-solving skills - Have excellent verbal and written communication skills, able to convey design decisions in both technical and layman's terms - Familiarity with data pipeline workflow tools like Apache Airflow or similar - Background in performance tuning for data systems, including caching, indexing, and database optimization Why Join Us Our flat organizational structure promotes teamwork across the Firm and offers easy access to senior staff. While we work exceptionally well as a team in the office, our bonds are further strengthened through company events, activities and giving back. Volleyball, soccer, hockey, 5K runs, picnic, parties, and trivia nights provide friendly competition and build better relationships. By getting out of our usual environment and doing out-of-the-ordinary things together, we foster creativity and broaden our imaginations to accomplish new challenges. Benefits: - Highly competitive salary & bonus opportunity - Generous paid time off and flexible scheduling - 100% coverage of medical, dental, vision, life, and disability benefits for single coverage - Generous Paid Parental Leave - Retirement Plans: 401K and Roth 401K - Profit sharing plan - Long- and short-term disability Additional Perks: - Free breakfast and lunch from our in-house kitchen with rotating menus (including snacks!) - On-site gym with a subsidized membership - Frequent company outings - Opportunity to give back to organizations that help individuals in need in the Chicagoland area Professional Development: - In-house education team - classes and resources are offered for continuous learning opportunities - Mentorship Program through your first six months of employment The base compensation range for this role is approximately $80,000-$120,000 contingent on experience. Wolverine Trading's total compensation model includes base salary and an annual discretionary bonus.

Who we are Apartment List is the premier rental matchmaker, connecting ready-to-move renters with compatible city properties. Our renters benefit from cutting-edge technology and a personalized approach when we match them with curated properties that fit their wishlist. Meanwhile, our supply partners harness our generative AI and machine learning to efficiently connect with our qualified renters. With performance-based pricing, our partners’ success is our success as we strive to deliver renters a home they love at the value they deserve. About the Role We are seeking a Senior Data Engineer (L3) to help build and operate the reliable, scalable data systems that power analytics, experimentation, and decision-making across Apartment List. In this role, you will be a strong end-to-end executor responsible for delivering production-grade data pipelines and workflows that meet defined service-level agreements (SLAs) for freshness, quality, and cost. You will work closely with Analytics Engineering, Data Science, Product, and Engineering partners to deliver durable data platform improvements that support company-wide initiatives. The ideal candidate is comfortable owning medium-sized data platform projects end-to-end—from design through deployment and operational support—while working within established platform architecture and engineering patterns. This role emphasizes execution excellence, reliability, and operational ownership within existing platform standards. Platform-level architecture and system design are owned at more senior levels, but this role plays a critical part in ensuring that the platform functions reliably at scale. Responsibilities - Design, build, test, and deploy scalable and reliable data pipelines that power analytics and product decision-making. - Own medium-sized data platform initiatives end-to-end, from initial design through production deployment and operational support. - Design, migrate, and maintain data workflows in Apache Airflow, including supporting migration of legacy ETL systems to modern orchestration patterns. - Ensure pipeline reliability by proactively monitoring workflow SLAs for freshness, quality, and performance, and resolving failures efficiently. - Implement and utilize monitoring systems to detect pipeline failures, schema drift, and data quality anomalies. - Participate in on-call rotations and contribute to incident response and root cause analysis for data incidents. - Apply best practices in warehouse performance and cost optimization, including partitioning, indexing, and efficient data modeling to control BigQuery spend. - Build maintainable, modular data models and pipelines using reusable patterns and shared components across the team. - Partner closely with Analytics Engineering, Data Science, and business stakeholders to deliver durable improvements across the ingestion, transformation, modeling, and serving layers of the data platform. - Contribute to operational excellence through documentation, monitoring improvements, and participation in postmortems and reliability initiatives. Key Qualifications & Competencies - 5+ years of experience in data engineering, with a track record of delivering reliable production data pipelines and systems. - Strong experience designing and maintaining orchestration workflows using Apache Airflow. - Experience building scalable data pipelines using modern cloud data platforms such as BigQuery and tools such as DBT. - Strong understanding of data modeling, schema design, and building maintainable, modular data systems. - Experience implementing CI/CD best practices for data pipelines, including automated testing, validation, and deployment workflows to ensure reliable and repeatable production releases. - Experience monitoring and operating production data systems, including pipeline observability, data quality checks, and incident response. - Ability to identify performance and cost risks in large-scale data systems and implement optimizations. - Strong collaboration skills and experience working with cross-functional partners including analytics engineers, data scientists, and product teams. - Proven ability to independently execute medium-sized projects and deliver reliable, production-grade systems. Nice-to-haves - Familiarity with Kubernetes-based data infrastructure, including deploying and operating containerized data services and workflows in a production environment. - Experience migrating legacy ETL systems to modern orchestration frameworks. - Familiarity with observability and monitoring tools for data pipelines (e.g., Datadog or similar). - Experience operating data systems with strict SLAs for freshness, reliability, and cost efficiency. Here's the Pay Range: At Apartment List, we carefully consider a variety of factors to determine compensation for each position, including the role, level, and work. The US Total Target Compensation (TTC) for this position is: - Zone 1: $148,000 - $180,000 TTC (including $133,000 - $158000 base salary) + equity - Zone 2: $137,000 - $167,000 TTC (including $123,000 - $147,000 base salary) + equity - Zone 3: $126,000 - $153,000 TTC (including $113,000 - $135,000 base salary) + equity This reflects the compensation target for new hire salaries for the position across all US locations. Please note, the compensation details provided do not include benefits and perks that we offer. We also rely on market indicators along with considering your work location, job related skills, experience and relevant education and training, to determine compensation that is fair and competitive for you. Apartment List will consider paying compensation near the higher of the range in exceptional circumstances, where candidates have the experience, credentials or expertise that would warrant such consideration. It is always our goal to hire exceptional talent and we would be happy to share more about compensation during the hiring process.

• Utilize SQL and data transformation tools (like DBT and Coalesce) to develop and deploy abstracted data models following the “Medallion” concept (Bronze, Silver, Gold) • Leverage Snowflake features (data sharing, dynamic tables, RBAC, Notebooks, Streamlit apps, Workspaces, Cortex, etc.) to provide reliable and efficient access to models • Collaborate with other engineering teams as well as business analysts and end-users to develop requirements and design useful data models • Clean up and translate legacy SQL logic and data models for a new unified representation system • Develop DAGs in Apache Airflow for delivering data products to internal and external partners • Manage Snowflake and Airflow related infrastructure with Terraform • Perform other duties as assigned