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Dotdash Meredith · 1 month ago

Data Operations Manager, D/Cipher

New York, NY - 225 Liberty Street

Full-time

Hybrid

Senior Level

$200K/yr - $215K/yr

7+ years exp

Dotdash Meredith is a leading digital media company, and they are seeking a Data Operations Manager for D/Cipher. This role involves leading a team of Data and Software Engineers to optimize data infrastructure, ensuring data accuracy and accessibility while driving continuous improvement across data workflows.

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Responsibilities

Lead and mentor a mixed team of Data and Software Engineers responsible for developing and optimizing scalable data pipelines, ensuring timely and reliable delivery of data for analytics and reporting

Partner with product managers and business stakeholders to define requirements and deliver high-quality, reliable datasets for use in Looker and other reporting tools

Enhance observability and reliability across the data platform by defining SLAs, data quality checks, and robust alerting mechanisms to support business reporting

Identify opportunities to improve data workflows, from ingestion to visualization, to empower teams with faster access to accurate insights

Evaluate and introduce new tools or techniques to strengthen the team’s operational capabilities

Drive alignment between engineering, product, and business teams, helping translate strategic priorities into measurable, data-driven outcomes

Oversee the evolution of our data lakes and data marts, driving continuous performance and cost optimization

Implement and maintain orchestration workflows, ensuring that ETL and ELT processes are automated, efficient, and resilient

Champion data engineering best practices through code reviews, process improvements, and the adoption of scalable architecture

Collaborate with security, infrastructure, and analytics teams to ensure data governance, compliance, and stability within a multi-cloud environment (GCP and AWS)

Qualification

Data engineeringPythonSQLGoogle Cloud PlatformAWSData lakes/warehousesETL/ELT processesData transformation toolsLeadershipCommunication

Required

7+ years of experience in data engineering or software development, with 2+ years of people management or technical leadership

Strong proficiency in Python and SQL, with hands-on experience building and optimizing data pipelines

Deep familiarity with Google Cloud Platform (BigQuery, Pub/Sub, Cloud Composer) and working knowledge of AWS

Experience designing and maintaining data lakes/warehouses

Knowledge of batch processing techniques using an orchestration framework, like Airflow

Experience with modern data transformation and modeling tools such as dbt, including an understanding of data lineage, dependency management, and version-controlled transformation workflows

Demonstrated ability to collaborate across functions and mentor engineers in a growth-oriented environment

Strong technical foundation in data architecture, ETL/ELT development, and cloud-native data solutions

Well-versed in BigQuery performance/cost optimization strategies

Excellent leadership and communication skills, with a focus on empowering teams and delivering measurable business impact

Bachelor's degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience