Intermediate Data Engineer (Contract)

Below is a ready‑to‑copy application package you can paste into the ParentsTogether online portal (or attach as separate files).
Feel free to tweak the wording, add your own project details, and replace the placeholder references with real contacts before you submit.

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1️⃣ Resume (PDF / DOCX)

[Your Full Name]
Data Engineer | Python | SQL | AWS/GCP | dbt | Power BI
[City, State] • [Phone] • [Email] • [LinkedIn] • [GitHub]

Professional Summary

Intermediate‑level data engineer with 4 + years of hands‑on experience designing, building, and maintaining scalable data pipelines on AWS and GCP. Proven track record of improving warehouse performance (up to 30 % query speed gains) using dbt, Snowflake/Redshift, and Python‑based ETL. Strong background in data modeling, version‑controlled analytics (Git + dbt), and delivering production‑ready Power BI dashboards for cross‑functional product teams. Passionate about empowering mission‑driven organizations with reliable data infrastructure.

Core Competencies

• Languages & Tools: Python (pandas, sqlalchemy, airflow), SQL (PostgreSQL, Snowflake, Redshift, BigQuery), dbt, Git, Docker, CI/CD (GitHub Actions)
• Cloud Platforms: AWS (S3, Lambda, Glue, Redshift, Athena), GCP (Cloud Storage, Cloud Functions, BigQuery)
• Data Modeling & Warehousing: Star/Snowflake schemas, dimensional modeling, data vault, incremental loads, partitioning & clustering
• BI & Visualization: Power BI (dataflows, DAX, row‑level security), Looker (optional)
• Data Ops: Monitoring (Airflow, Dagster, CloudWatch), alerting, data quality testing (Great Expectations), documentation (dbt docs, Confluence)
• APIs & Scraping: RESTful APIs (Twitter, Facebook, Instagram), OAuth, Selenium/Playwright for web scraping
• Governance & Security: IAM policies, encryption at rest/in‑transit, GDPR/CCPA awareness

Professional Experience

Data Engineer – [Current / Most Recent Employer] – [City, State]
MM/YYYY – Present

• Designed and deployed 15+ end‑to‑end ELT pipelines using dbt + Airflow on AWS Redshift; reduced data latency from 24 h to < 2 h.
• Migrated legacy on‑prem warehouse to Snowflake, re‑architected schemas, and implemented incremental models, achieving 30 % faster query performance and 20 % cost reduction.
• Built Power BI dataflows & dashboards for product, marketing, and finance teams; introduced row‑level security and automated refresh schedules.
• Implemented Git‑based version control for all dbt projects; set up CI pipelines that run schema tests and generate documentation on every PR.
• Developed a social‑media ingestion framework (Twitter API v2, Instagram Graph API) that pulls daily engagement metrics into the warehouse, supporting audience‑growth analytics.

Data Analyst / Junior Data Engineer – [Previous Employer] – [City, State]
MM/YYYY – MM/YYYY

• Created SQL‑based data models for a 10 TB data lake on Google BigQuery, optimizing partitioning and clustering to cut query costs by 25 %.
• Automated daily data quality checks with Great Expectations, reducing manual QA effort by 80 %.
• Produced Power BI reports for senior leadership, translating raw data into actionable insights on user acquisition and retention.

Intern – [Earlier Role] – [City, State]
MM/YYYY – MM/YYYY

• Assisted in building a Python‑based web scraper for public education data; stored results in AWS S3 and loaded into Redshift via AWS Glue.

Education

B.S. in Computer Science – [University Name], [City, State] – Graduated MM/YYYY

Certifications (optional)

• AWS Certified Data Analytics – Specialty
• dbt Fundamentals (dbt Labs)
• Microsoft Certified: Data Analyst Associate (Power BI)

References (available on request)

1. [Name], Lead Data Engineer – [Company] – [Phone] – [Email]
2. [Name], Senior Product Manager – [Company] – [Phone] – [Email]

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2️⃣ Brief Summary of Relevant Experience (≈ 150‑200 words)

I am a data engineer with 4 years of experience building production‑grade pipelines for fast‑growing consumer‑facing organizations. At my current role I migrated a legacy on‑prem data warehouse to Snowflake, re‑designed the data model using dbt, and cut query latency by 30 % while lowering monthly compute spend by 20 %. I have extensive hands‑on experience with Python, SQL, AWS (S3, Lambda, Redshift, Glue) and GCP (BigQuery, Cloud Functions), and I routinely use Git‑based version control for all data‑engineering artifacts.

I have built and maintained Power BI dashboards for product, marketing, and finance teams, implementing row‑level security and automated refresh pipelines. My recent project involved creating a social‑media ingestion framework that pulls daily metrics from the Twitter and Instagram APIs, normalizes them with dbt, and makes them available for real‑time analytics. I am comfortable working from the command line, troubleshooting pipeline failures, and documenting architecture for cross‑functional stakeholders.

I am excited about ParentsTogether’s mission to empower families and believe my technical background, collaborative mindset, and passion for data‑driven impact will help the organization scale its data infrastructure efficiently.

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3️⃣ Weekly Availability (example)

Day (ET)	Availability (hours)
Monday	2 pm – 5 pm (3 h)
Tuesday	12 pm – 5 pm (5 h)
Wednesday	12 pm – 4 pm (4 h)
Thursday	1 pm – 5 pm (4 h)
Friday	12 pm – 3 pm (3 h)

Total: ~ 19 hours/week (flexible; can shift up to 10 hours/week to meet the 10‑hour target as needed). I can adjust my schedule to align with the preferred 12 pm – 5 pm ET collaboration window.

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4️⃣ Professional References (template)

1. [Full Name] – Lead Data Engineer, [Company]
   • Phone: [xxx‑xxx‑xxxx]
   • Email: [firstname.lastname@company.com]
   • Relationship: Direct manager for 2 years; supervised data‑pipeline projects and warehouse migrations.

2. [Full Name] – Senior Product Manager, [Company]
   • Phone: [xxx‑xxx‑xxxx]
   • Email: [firstname.lastname@company.com]
   • Relationship: Cross‑functional partner on analytics dashboards and data‑product roadmaps.

(Add a third reference if the portal asks for more.)

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How to Submit

1. Upload the PDF version of the resume.
2. Copy‑paste the “Brief Summary of Relevant Experience” into the designated text box on the application form.
3. Enter the weekly availability table (or a short paragraph) in the “Availability” field.
4. Provide the two (or three) references in the “References” section, or attach a separate document if the portal allows.

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Quick Checklist Before You Hit “Submit”

• ☐ Resume is saved as PDF (fonts embedded, no hidden personal data).
• ☐ Summary is ≤ 200 words and highlights Python, SQL, dbt, AWS/GCP, Power BI.
• ☐ Availability aligns with the 12 pm – 5 pm ET window.
• ☐ References have been contacted and consented to be listed.
• ☐ All required fields on the portal are filled (e.g., contact info, legal eligibility).

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Good luck! 🎉
If you’d like a deeper review of any part of the application (e.g., tailoring the resume bullet points to a specific project you’ve done, or preparing for the CoderPad technical exercise), just let me know—I’m happy to help.