Company logo

Marketing Data Analyst – Advanced Data & Visualization Specialist

Dynamed Healthcare Solutions Pvt.Ltd.

Kochi

in 4 days

The Marketing Data Analyst will play a critical role in transforming raw data from various sources into insightful visualizations and reports, supporting data-driven marketing strategies. This role demands expertise with cloud-based data platforms and advanced visualization tools to manage and present complex marketing datasets. The ideal candidate will have strong analytical skills, technical proficiency in data extraction and transformation, and experience in presenting actionable insights that inform and guide marketing strategies. Key Responsibilities

  1. Data Collection, Integration & Management ? Collect, clean, and integrate marketing data from various sources (e.g., Google Analytics, CRM, social media, paid advertising) into centralized data environments using platforms like Supermetrics and BigQuery. ? Work within Snowflake or similar cloud-based data warehousing solutions to manage large datasets, ensuring scalability and accessibility for ongoing analysis. ? Collaborate with data engineers to establish data pipelines and ETL processes that support seamless data integration across platforms.
  2. Data Visualization & Reporting ? Use Power BI, Tableau, and Google Data Studio to create interactive dashboards and reports that provide a clear, real-time view of key marketing metrics, including CTR, CPA, CAC, LTV, and conversion rates. ? Design user-friendly visualizations that enable stakeholders to quickly grasp campaign performance, audience behaviors, and trends. ? Customize dashboards for various audiences, from high-level overviews for leadership to in-depth performance reports for marketing teams.
  3. Advanced Analysis & Insights Generation ? Utilize SQL in BigQuery to query and manipulate large datasets, uncovering insights into campaign performance, customer journeys, and audience segmentation. ? Conduct attribution analysis, customer segmentation, and cohort analysis to guide marketing decisions and optimize campaign targeting. ? Regularly evaluate campaign data to identify trends, opportunities, and areas for optimization, providing actionable recommendations for improvement.
  4. Performance Metrics Tracking & Automation ? Set up automated data retrieval through Supermetrics to feed ongoing reports and dashboards with the latest marketing metrics. ? Track key performance indicators (KPIs) across marketing channels, including paid media, email marketing, content performance, and organic traffic. ? Conduct A/B testing analysis, evaluating results to support data-driven decisions on creative, audience, and placement strategies.
  5. Cross-Functional Collaboration ? Collaborate with marketing, product, and data engineering teams to ensure data accuracy, alignment on KPIs, and integration of new data sources as needed. ? Partner with stakeholders to define and adjust metrics, ensuring dashboards and reports meet evolving marketing objectives and data needs.
  6. Data Quality Control & Governance ? Implement data quality checks and maintain data hygiene, regularly auditing datasets to ensure accuracy and consistency across all reporting platforms. ? Establish best practices for data governance, documenting processes, and ensuring adherence to data security and privacy standards. Qualifications ? Experience: 4-6 years of experience as a Marketing Data Analyst, Data Analyst, or in a similar role focused on marketing analytics and data visualization. ? Technical Skills: ? Proficiency in Snowflake or similar cloud-based data warehousing platforms. ? Advanced skills in SQL (preferably with BigQuery) for data extraction and manipulation. ? Experience with Supermetrics for data pipeline management and automation. ? Expertise in visualization tools: Power BI, Tableau, and Google Data Studio. ? Familiarity with Google Analytics, social media analytics, and digital advertising platforms (e.g., Google Ads, Facebook Ads). ? Analytical Skills: Strong quantitative background, adept at interpreting large datasets and extracting actionable insights.