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Working as Data Engineer �in A Tech Company

Guest Speaker: Ada Li

10/14/2021

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Ada Li

Data Engineer at

OUTLINE

A TYPICAL DAY IN A TECH TEAM

WHAT IS DATA ENGINEERING

DIFFERENT POSITIONS IN A TECH TEAM

TIPS FOR JOB SEARCHING

Q&A

B.S. in MIS

M.S. in BA & CS

Good afternoon, WT friends,

And Thank you for the invitation and the nice intro, Dr. Zhang. It is my pleasure to be here. I’m Ada Li. I am currently a data engineer in Imagery team, at MapBox, which is a mapping and location cloud platform for developers. I’ve been working for Mapbox for about 1year and half now. Not so long ago, I was also a student myself, who had limited knowledge about what the tech industry looks like. Maybe some of you are having the same questions I had before.

So for today’s talk, I’m going to share my experience about working in a tech company, what’s my typical day looks like, what are some of the projects I’ve been working on;

and then, I will share a bit about different positions in a tech team, and what I feel most important to these roles,

and finally, I will share about how I did my job searching and things that helped me to increase my chance of landing my first job.

I’ll try to leave space for a Q&A to answer questions submitted ahead and live questions as well.

Before we start, a small disclaimer I’d like to make is that, like I said I am in the very early stages of my career, so everything I’m sharing here are based on my own experience and understanding so far. They are by no means of the ultimate guidelines here. So do take that into account and listen to more people’s thought when you build your own job searching strategy.

Okay, now let’s get started- (click)

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A TYPICAL DAY IN A TECH TEAM

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A TYPICAL DAY IN A TECH TEAM

Lunch & Nap

My

Morning:
Typically, I would start my day around 9 with a cup of coffee. I got online and check messages on Slack, emails and scheduled meetings on my Calendar to plan my day. Then, we would do a virtual async standup in the team slack channel, which means we post our plans for the day in text format. For my team, we like to keep our meetings to the minimum and do more async work, because our teammates span across different time zones in the US and it’s just easier to manage for everyone. For my summer internship in another company, when I did work in an office, we would have the standup meeting together. This is basically, how my everyday starts.
Then I start writing some coding, creating pull requests, doing code reviews, documentations, with some music on if I’m in the mood. And that’s usually the time I’m mostly focused.
Noon:
Then it’s lunch time. I’d make sure I post in slack to let people know whenever I’m away from keyboard, taking a break or making a quick run to the grocery.
Afternoon:
When I get back in the afternoon, this is usually when most of my meeting happens.

We would have weekly team sync up to make plans and set priorities for the week
mid-week technical sync to unblock each other as much as we can
biweekly team reviews for better team operations purposes
company all-hands, usually monthly
and also there’s weekly 1-1 with my manager
and Pair programming sessions with coworkers if needed
We have also set up a space for Casual Hangout with the team to just socialize and taking a break from work, and it’s completely optional if you want to focus on your work during that time.

If I don’t have a meeting, then I’d go back to more coding. Take breaks whenever I need one. Health is important as well. Usually around 5pm I’d start to wrap up for the day and prep for dinner. And that’s my day.

For the coding part, I’m the point person for the team’s Metrics and Data Engineering related work, and broadly responsible for the creation and operation of data pipelines and infra used to understand and sustain Imagery services and customers. So what is data engineering then?

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WHAT IS DATA ENGINEERING

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WHAT IS DATA ENGINEERING

PIPELINES

DATA

Data

End Storage

Data

Transformation

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Airflow Pipeline

https://images.ctfassets.net/fi0zmnwlsnja/6NglzN2XUTFO5snsIcKIM/2d528578d42ae86a3fe71e0cf56c6770/amazon-athena-cover.png

This Photo by Unknown Author is licensed under CC BY-SA-NC

Data Warehouse

Spark Tasks

Python Tasks

Workflow Management

Endpoints for

Frontend Visualization

SQL Tasks

Raw Data

Processed Data

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Database Infra and Ingestion

Amazon Simple Storage Service (S3)

Store data with different:

Location
File name
Format
Structure

Amazon Relational Database Service (RDS)

AWS Lambda

Event-driven, Serverless

Computing Platform

AWS CloudFormation

Data Ingestion

Amazon CloudWatch

Performance Monitor

This Photo by Unknown Author is licensed under CC BY-SA

Amazon Elastic Compute Cloud (EC2) Internal Access to RDS

Existing Data

Frontend

SQL Query, Cross-team Access

Incoming Data

This Photo by Unknown Author is licensed under CC BY-SA

Amazon Simple Queue Service (SQS)

Message Queuing Service

Data Ingestion

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DIFFERENT POSITIONS IN A TECH TEAM

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Software Engineer

Responsibilities

Design, develop, test, deploy, maintain and improve software

Skill highlights

Programming language
Data Structures and Algorithms
Computer science fundamentals
…

Different tracks

Web development (front-end/back-end/full stack)
Mobile development (iOS/Android)
SRE/DevOps
Test related roles
Other domain specific roles(e.g., ML, NLP, CV, AI, data, etc.)

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Data Engineer

Responsibilities

Develop data infrastructure and data pipelines
Extract data from various data sources
Transform and load data into a data storage system

Skill highlights

SQL and Programming language
Data Structures and Algorithms
Data storage/data infrastructure/data handling framework
…

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Data Scientist

DS: Data Scientist

generally, have a Ph.D. degree

Responsibilities

Collaborate with a team of engineers, analysts and PMs on a wide range of problems to improve quality of products/services
Estimate the unknown by asking questions, writing algorithms, and building statistical models

Notes

Some roles may require a Ph.D. degree.
“Data Scientist” varies a lot from company-to-company.

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Business/Data Analyst

Skills

Domain Knowledge: Business/Supply Chain/Finance, etc.
Data visualization tools or platforms (e.g. Tableau)
Statistical tools and A/B testing
…

Responsibilities

Examine large data sets to identify trends, develop charts, and create visual presentations to help businesses make more strategic decisions.

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RELATIONS AMONG MAJORS

Computer Science

Information System

Analytics

Management

Software

Development

Decision

Making

Data Modeling

Data Mining

Visualization & Reporting

Interpretation

into insights

Data Scientist

Software Engineer

Data Engineer

Business/Data Analyst

Information

Retrieving

Information

Storing

Information

Processing

Technical

Business

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TIPS FOR JOB SEARCHING

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ABOUT JOB SEARCHING

General Tech Interview Process

Resume Preparation

LinkedIn/GitHub
Internship
Related projects
Network referral

HR Phone Screen

Technical Interview

Onsite Interview

Resume Screening

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ABOUT JOB SEARCHING

General Tech Interview Process

Phone Screen

Job Description
Company Info.
Details of your resume
Your background
Sponsorship (Visa status)

HR Phone Screen

Technical Interview

Onsite Interview

Resume Screening

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ABOUT JOB SEARCHING

General Tech Interview Process

Virtual Interview

Hard skills
Coding and Algorithm (SE, DE)
Case studies, Statistics (BA, DA)
Working/project experience
Behavior questions

HR Phone Screen

Technical Interview

Onsite Interview

Resume Screening

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ABOUT JOB SEARCHING

General Tech Interview Process

In office or Online

last for several hours to a full day
3-4 tech interviews + 1 BQ interview

HR Phone Screen

Technical Interview

Onsite Interview

Resume Screening

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TIPS FOR JOB SEARCHING

My takeaways:

Make a spreadsheet to track all your applications and interview progress.
Customize your resume to the roles you apply.
Practice your self-introduction and behavior questions.
Do mock interviews with friends.
Think out loud when solving coding problems!
Be confident and keep trying.

Job search resources:

Companies career page, Linkedin, Indeed, Anglelist, Handshake, GHC(Grace Hopper Celebration of Women in Computing), School Career fair, company info sessions at school, referrals, …

NEVER GIVE UP!

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Q&A

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Questions

What career advice tips can you provide to a senior or graduate-level student?

How do you land a job when you have zero experience in the related field?

Outside resources to get started?

How do you practice or prepare the communication of your work to others whether they are technically or non-technically knowledgeable?

How do you make sure that the insight you gain from data is communicated well?

Do you work closely with a data scientist to do this or is the interpretation of data a data scientist's job?

Personally speaking:

For short term career plans, make sure you have a solid foundation in your interested field. Sometimes, you’re are expected more than undergrads when doing interviews. If you are not sure about what you are most interested in at the moment, that’s ok. Find internships to give it a try them out.

In the long term:

a mentor, always be growing and learning, be an expert on your interested field.

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Internships are good experience. “Don’t be too picky about the first job.”

Course project, Kaggle competition, side projects.

Online coding competition/Hackathon

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Learn from others. See how others communicate and learn from them.

For tech or non-tech conversations, I find making a shared doc to put down notes and thoughts, both before and during the conversation could be helpful. Check in with the folks you are talking to, make sure the convo go back and forth. Not just you talking.

Provide better visual presentation. Graph and visual displays speak louder than words. Sharescreen if necessary. Show your ideas interactively rather than simply talking through.

For my team, we don’t have a ds. I’d do some of the analytics work like visualizations and experimental research on understanding our customers.

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Thank you!

Guest Speaker: Ada Li

10/14/2021

Would you please provide your comments

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